Dam body seepage flow automatic monitoring method and system and electronic equipment

Abstract

The invention provides a dam body seepage flow automatic monitoring method and system and electronic equipment. The method comprises the steps that seepage weight data information collected by a weight sensor is sent to an area controller through a collection board; the management system calculates seepage flow receiving duration data, flow data and seepage flow data in unit time according to the transmitted seepage weight data information; the management system collects seepage flow data of each time node and preprocesses the collected data; the management system carries out trend analysis on the seepage flow data; the management system predicts future changes in the seepage flow. The automatic data acquisition and processing mechanism improves the monitoring efficiency of the seepage flow, reduces data errors caused by manual operation, and can use the time sequence prediction model to predict the long-term trend of the seepage flow, which is helpful for identifying potential risk points and improving the accuracy of the prediction result. The accuracy and the intelligent level of dam body seepage flow monitoring are improved, and an effective technical guarantee is provided for safe operation of a dam.

Description

Technical Field

[0001] The invention relates to the technical field of water conservancy dam seepage detection, and in particular to an automatic monitoring method, system and electronic equipment for dam body seepage. Background Art

[0002] In the field of water conservancy projects, dam safety monitoring is a key link to ensure its normal operation and prevent disasters. Among them, the monitoring of dam seepage is crucial to assessing the stability of the dam and preventing potential risks caused by leakage. However, existing seepage monitoring technologies mostly rely on manual operations. These methods are not only inefficient, but also difficult to ensure the accuracy and reliability of the measurement results due to the intervention of human factors. Traditional manual monitoring methods usually involve the following steps: first, a seepage collection device is set at a specific location on the dam body; then, the staff collects seepage samples regularly or irregularly; finally, the seepage of the dam body is estimated by measuring the collected seepage. This method has the following main problems: 1. Efficiency problem. Manual monitoring requires frequent on-site operations, which consumes a lot of manpower and time. Especially in large-scale water conservancy projects, the monitoring workload is huge. 2. Accuracy problem: Manual measurement is easily affected by the operator's technical level, environmental factors and the accuracy of the measuring tool, resulting in large errors in the measurement results; 3. Real-time problem: Due to the intermittent nature of the monitoring process, it is difficult to achieve real-time monitoring of the dam seepage, which may lead to delays in risk assessment and response measures in emergency situations. In view of the above problems, the existing technology urgently needs an automated, efficient and accurate seepage monitoring method to improve the efficiency and accuracy of monitoring, reduce the risk of manual operation, and realize real-time monitoring of the seepage condition of the dam body. Summary of the invention

[0003] In order to solve the current technical problems, the main purpose of the present invention is to provide an automatic monitoring method, system and electronic equipment for dam seepage, which can not only significantly improve the monitoring efficiency of dam seepage, but also realize real-time monitoring and data analysis of dam seepage conditions, thereby providing more reliable technical support for the safe operation and maintenance of the dam.

[0004] The technical solution adopted by the present invention is: a method for automatically monitoring the seepage volume of a dam body, comprising the following steps: The water seepage weight data information collected by the weight sensor is sent to the regional controller through the acquisition board; The regional controller sends the data information to the management system, and the management system stores the data information in a database; The management system calculates the seepage volume access time data, flow data and seepage volume data per unit time based on the transmitted seepage water weight data information, and stores the data in the database; The management system collects the seepage data at each time node and pre-processes the collected data; The management system conducts descriptive statistical analysis on the mean, median and standard deviation of seepage volume; The management system uses a charting tool to draw a line chart showing the change of seepage volume over time; The management system performs trend analysis on the seepage data; The management system predicts future changes in seepage volume.

[0005] The acquisition board is connected to the regional controller via the CANbus protocol, and the weight sensor sends the water seepage weight data to the regional controller via the acquisition board. The CANbus protocol has an error monitoring and arbitration mechanism.

[0006] The zone controller is in communication connection with the management system, and the data information storage includes a timestamp to record the specific time of each piece of data information.

[0007] The management system calculates the seepage volume access time based on the transmitted seepage weight data ,flow And the seepage rate within one minute .

[0008] The seepage flow access time Obtained by the following formula: ; In the formula, is the current timestamp, is the timestamp of when monitoring starts; The flow rate Q is obtained by the following formula: ; In the formula, Represented as a timestamp The weight of the collected seepage water; Represented as a timestamp The weight of the collected seepage water; Expressed as the density of water; Represented as a timestamp To timestamp time difference; Percolation within one minute Obtained by the following formula: ; In the formula, Expressed as a unit of time, that is, one minute.

[0009] The preprocessing includes removing outliers, filling missing values, and data standardization.

[0010] The average value M of the seepage volume is obtained by the following formula: ; In the formula, is the ith data point, is the total number of data points; The median calculation is to arrange the data points in order of size. If the number of data points is an odd number, the median is the middle value; if the number of data points is an even number, the median is the average of the two middle values; The standard deviation S is obtained by the following formula: ; In the formula, Represents the seepage data points recorded at a specific time; i represents the total number of observations in the data set; Represents the total number of observations in the dataset.

[0011] The management system identifies trends in seepage data, including increases, decreases or cyclical changes, by analyzing charts.

[0012] The management system applies a time series analysis solution and uses a time series prediction model to predict future changes in seepage volume.

[0013] A dam body seepage flow automatic monitoring system, used to implement a dam body seepage flow automatic monitoring method, comprising: A collection module, used to collect water seepage weight data from a water seepage collection device; An interactive module, used for receiving water seepage weight data and transmitting the data to a management system; A storage module, used for storing water seepage weight data; Analysis module, used to convert water seepage weight data into volume and analyze water seepage data trends.

[0014] An electronic device comprises a memory, a processor and a computer program stored in the memory and executable on the processor, wherein the processor executes the steps of a method for automatically monitoring the seepage flow of a dam body.

[0015] The present invention has the following beneficial effects: The present invention integrates a weight sensor and a seepage collection device connected to a regional controller via a CANbus communication protocol, and the regional controller is connected to a management system to achieve real-time monitoring of the seepage situation of the dam. The weight sensor is responsible for collecting seepage data, and the CANbus communication protocol ensures that these data can be quickly and accurately transmitted to the management system. The automated data collection and processing mechanism improves the monitoring efficiency of the seepage volume and reduces data errors caused by human operation.

[0016] On the other hand, the management system includes descriptive statistical analysis, which is used to preliminarily organize and analyze the collected seepage data to identify the basic characteristics and distribution of the data, and use the time series prediction model (ARIMA model) to predict the long-term trend of seepage, which helps to identify potential risk points. Through these technical means, managers can gain an understanding of the current seepage conditions and make scientific decisions and plans based on the prediction results, which improves the accuracy and intelligence level of dam seepage monitoring and provides effective technical guarantees for the safe operation of the dam. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] In order to more clearly illustrate the specific implementation methods of the present invention or the technical solutions in the prior art, the drawings required for use in the specific implementation methods or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are some implementation methods of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0018] Figure 1 The figure is a flow chart of the automatic monitoring method of the present invention.

[0019] Figure 2 It is a module diagram of the automatic monitoring system of the present invention. DETAILED DESCRIPTION

[0020] The technical solution of the present invention will be described clearly and completely below in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0021] Embodiment 1: See also Figure 1 The present invention provides a method for automatically monitoring dam body seepage, comprising the following steps: S1, sending the seepage weight data information collected by the weight sensor to the regional controller through the acquisition board; S2. The regional controller sends the data information to the management system, and the management system stores the data information in the database; S3, the management system calculates the seepage volume access time data, flow data and seepage volume data per unit time according to the transmitted seepage water weight data information, and stores the data in the database; S4, the management system collects the seepage data at each time node and pre-processes the collected data; S5. The management system conducts descriptive statistical analysis on the mean, median and standard deviation of the seepage volume; S6. The management system uses a chart tool to draw a line chart of seepage flow rate changing over time; S7. The management system performs trend analysis on the seepage data; S8. The management system predicts future changes in seepage volume.

[0022] In S1, a weight sensor and a collection board are provided in the water seepage collection device, the weight sensor is electrically connected to the collection board, and the collection board is communicatively connected to the regional controller. Specifically, the collection board is connected to the regional controller via the CANbus protocol, and the weight sensor sends the water seepage weight data in the water seepage collection device to the regional controller via the collection board. The CANbus protocol supports real-time data communication, ensuring that the collection board can quickly transmit the water seepage weight data collected by the weight sensor to the regional controller. The CANbus protocol has an error monitoring and arbitration mechanism, which can ensure the accuracy and reliability of data transmission and reduce the risk of data loss or errors.

[0023] In S2, the regional controller is connected to the management system for communication. The management system receives data from the regional controller and stores it in a database. The data storage includes a timestamp to record the specific time of each data record.

[0024] In S3, the management system calculates the seepage flow access time based on the transmitted seepage weight data ,flow And the seepage volume collected in the collection device within one minute .

[0025] In one of the schemes, the capacity of the seepage collection device is 400 ml. When the seepage volume reaches or exceeds 400 ml, the timestamp at that time is recorded. , duration is the timestamp from the first measurement arrive The time difference is obtained by the following formula: ; in, is the current timestamp, is the timestamp of when monitoring starts; The flow rate Obtained by the following formula:

[0026] in, Represented as a timestamp The weight of the collected seepage water; Represented as a timestamp The weight of the collected seepage water; Expressed as the density of water; Represented as a timestamp To timestamp time difference; The amount of seepage collected in the sampling device within one minute Obtained by the following formula: ; in, Expressed as a unit of time, that is, one minute.

[0027] The duration ,flow And the seepage volume collected in the collection device within one minute The data is stored in the database and the change trend of seepage volume over time is analyzed to predict possible risks and future flow changes, so as to facilitate the query and analysis of historical data.

[0028] In S4-S5, the management system analyzes the seepage change trend through the following steps: The management system collects hourly seepage data and pre-processes the collected data, including removing outliers, filling missing values, and data standardization; The management system performs descriptive statistical analysis on the mean, median and standard deviation of water seepage; The average water seepage value M of the management system is first summed up all the flow data, and the sum is divided by the number of data points to get the average value. The average value provides the center position of all data points in the data set and is obtained by the following formula: ; in, is the ith data point, is the total number of data points.

[0029] The median calculation is to arrange the data points in order of size. If the number of data points is an odd number, the median is the middle value; if the number of data points is an even number, the median is the average of the two middle values. The median is the center point of the data, which is not affected by extreme values ​​or outliers and is a robust measure of non-central tendency.

[0030] The standard deviation of the management system provides the fluctuation of the seepage volume, which is helpful to understand the stability and risk assessment of the seepage. The standard deviation S is obtained by the following formula: ; in, Represents the seepage data points recorded at a specific time; irepresents the total number of observations in the data set; Represents the total number of observations in the dataset.

[0031] In S6, a line graph of the seepage volume over time is drawn using a chart tool to visually display the trend. The management system extracts the seepage volume data and the corresponding timestamps from the database, and uses Python chart tools to draw these data points on the coordinate axis in chronological order to form a continuous line, thereby generating a line graph that visually displays the seepage volume over time. This graph can be integrated into the management interface, allowing users to perform interactive operations such as zooming and panning to view the data change trend of a specific time period in detail.

[0032] In S7, the trend of the data, including rising, falling or cyclical changes, is initially identified by visually inspecting the chart. The historical data of seepage volume is extracted and preprocessed from the database to ensure the accuracy and completeness of the data. The time series analysis method is used to identify the trend lines and cyclical patterns in the data. The ARIMA model is used to conduct in-depth analysis of the data to predict future seepage volume changes.

[0033] In S8, a time series analysis scheme is applied, and the ARIMA model is used to predict the future changes of the seepage volume. Specifically, historical seepage volume data is extracted from the database, and then the prediction model ARIMA is trained using the data, and the ARIMA model is used to predict the changes of the seepage volume in the future time period.

[0034] The present invention integrates a weight sensor and a seepage collection device connected to a regional controller via a CANbus communication protocol, and the regional controller is connected to a management system to achieve real-time monitoring of the seepage situation of the dam. The weight sensor is responsible for collecting seepage data, and the CANbus communication protocol ensures that these data can be quickly and accurately transmitted to the management system. The automated data collection and processing mechanism improves the monitoring efficiency of the seepage volume and reduces data errors caused by human operation.

[0035] On the other hand, the management system includes descriptive statistical analysis, which is used to preliminarily organize and analyze the collected seepage data to identify the basic characteristics and distribution of the data, and use the time series prediction model (ARIMA model) to predict the long-term trend of seepage, which helps to identify potential risk points. Through these technical means, managers can gain an understanding of the current seepage conditions and make scientific decisions and plans based on the prediction results, which improves the accuracy and intelligence level of dam seepage monitoring and provides effective technical guarantees for the safe operation of the dam.

[0036] Embodiment 2: See also Figure 2The present invention provides a dam body seepage automatic monitoring system, comprising: A collection module, used to collect water seepage weight data from a water seepage collection device; An interactive module, used for receiving water seepage weight data and transmitting the data to a management system; A storage module, used for storing water seepage weight data; Analysis module, used to convert water seepage weight data into volume and analyze water seepage data trends.

[0037] Embodiment three: The present invention provides an electronic device, comprising a memory, a processor and a computer program stored in the memory and operable on the processor, wherein the processor executes steps of a method for automatically monitoring the seepage volume of a dam body.

[0038] It should be noted that, unless otherwise specified herein, there is no strict order restriction for the execution of these steps, and these steps may be executed in other orders. Moreover, at least a portion of the steps may include multiple steps or multiple stages, and these steps or stages are not necessarily executed at the same time, but may be executed at different times, and the execution order of these steps or stages is not necessarily sequential, but may be executed in turn or alternately with other steps or at least a portion of the steps or stages in other steps.

[0039] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present application may adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program codes.

[0040] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1These computer program instructions can also be stored in a computer-readable memory that can guide a computer or other programmable data processing device to work in a specific way, so that the instructions stored in the computer-readable memory produce a product including an instruction device, which implements the functions specified in the process. Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0041] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0042] The above is only a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the technical principles of the present invention. These improvements and modifications should also be regarded as the scope of protection of the present invention.

[0043] The above description is only a preferred example of the present invention and is not intended to limit the present invention. Although the present invention is described in detail with reference to the aforementioned embodiments, those skilled in the art can still modify the technical solutions described in the aforementioned embodiments, or perform equivalent replacements on some of the technical features. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A method for automatically monitoring dam body seepage, characterized in that: The following steps are involved: The water seepage weight data information collected by the weight sensor is sent to the regional controller through the acquisition board; The regional controller sends the data information to the management system, and the management system stores the data information in a database; The management system calculates the seepage volume access time data, flow data and seepage volume data per unit time based on the transmitted seepage water weight data information, and stores the data in the database; The management system collects the seepage data at each time node and pre-processes the collected data; The management system conducts descriptive statistical analysis on the mean, median and standard deviation of seepage volume; The management system uses a charting tool to draw a line chart showing the change of seepage volume over time; The management system performs trend analysis on the seepage data; The management system predicts future changes in seepage volume.

2. The method for automatic monitoring of dam body seepage according to claim 1, characterized in that: The acquisition board is connected to the regional controller via the CANbus protocol, and the weight sensor sends the water seepage weight data to the regional controller via the acquisition board. The CANbus protocol has an error monitoring and arbitration mechanism.

3. The method for automatic monitoring of dam body seepage according to claim 1, characterized in that: The zone controller is in communication connection with the management system, and the data information storage includes a timestamp to record the specific time of each piece of data information.

4. The method for automatic monitoring of dam body seepage according to claim 1, characterized in that: The management system calculates the seepage volume access time based on the transmitted seepage weight data ,flow And the seepage rate within one minute ; The seepage flow access time Obtained by the following formula: ； In the formula, is the current timestamp, is the timestamp of when monitoring starts; The flow rate Q is obtained by the following formula: ； In the formula, Represented as a timestamp The weight of the collected seepage water; Represented as a timestamp The weight of the collected seepage water; Expressed as the density of water; Represented as a timestamp To timestamp time difference; Percolation within one minute Obtained by the following formula: ； In the formula, Expressed as a unit of time, that is, one minute.

5. The method for automatic monitoring of dam body seepage according to claim 1, characterized in that: The preprocessing includes removing outliers, filling missing values, and data standardization.

6. The method for automatic monitoring of dam body seepage according to claim 1, characterized in that: The average value M of the seepage volume is obtained by the following formula: ； In the formula, is the ith data point, is the total number of data points; The median calculation is to arrange the data points in order of size. If the number of data points is an odd number, the median is the middle value; if the number of data points is an even number, the median is the average of the two middle values; The standard deviation S is obtained by the following formula: ； In the formula, Represents the seepage data points recorded at a specific time; i represents the total number of observations in the data set; Represents the total number of observations in the dataset.

7. The method for automatic monitoring of dam body seepage according to claim 1, characterized in that: The management system identifies trends in seepage data, including increases, decreases or cyclical changes, by analyzing charts.

8. The method for automatic monitoring of dam body seepage according to claim 1, characterized in that: The management system applies a time series analysis solution and uses a time series prediction model to predict future changes in seepage volume.

9. A dam body seepage flow automatic monitoring system, used to implement a dam body seepage flow automatic monitoring method according to claims 1-8, characterized in that: include: A collection module, used to collect water seepage weight data from a water seepage collection device; An interactive module, used for receiving water seepage weight data and transmitting the data to a management system; A storage module, used for storing water seepage weight data; Analysis module, used to convert water seepage weight data into volume and analyze water seepage data trends.

10. An electronic device, characterized in that: The invention comprises a memory, a processor and a computer program stored in the memory and executable on the processor, wherein the processor executes the steps of the method for automatically monitoring the seepage flow of a dam body as described in claims 1 to 8.

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