A dam seepage flow automatic monitoring method, system and electronic equipment

Abstract

The present invention provides a method, system, and electronic device for automatically monitoring dam body seepage flow. The method uses an acquisition board to transmit seepage weight data collected by a weight sensor to a regional controller. The management system calculates seepage flow access duration data, flow data, and seepage flow data per unit time based on the transmitted seepage weight data. The management system collects seepage flow data at each time point and preprocesses the collected data. The management system performs trend analysis on the seepage flow data. The management system predicts future changes in seepage flow. The present invention's automated data acquisition and processing mechanism improves the efficiency of seepage flow monitoring while reducing data errors caused by human intervention. It can also use a time series prediction model to predict long-term seepage flow trends, which helps identify potential risk points, improves the accuracy and intelligence of dam body seepage flow monitoring, and provides effective technical support for the safe operation of the dam.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of water conservancy dam seepage flow detection, in particular to a dam body seepage flow automatic monitoring method, system and electronic equipment. BACKGROUND

[0002] In the field of water conservancy engineering, dam safety monitoring is a key link to ensure its normal operation and prevent disasters. Among them, the monitoring of dam body seepage flow is crucial for assessing the stability of the dam and preventing potential risks caused by seepage. However, existing seepage flow monitoring techniques rely heavily on manual operation, and these methods are not only inefficient, but also due to the intervention of human factors, the accuracy and reliability of the measurement results are difficult to guarantee. The traditional manual monitoring method usually involves the following steps: first, set up seepage water collection devices at specific locations of the dam body; then, the staff collects seepage water samples regularly or irregularly; finally, the seepage flow of the dam body is estimated by measuring the collected seepage water volume. This method has the following main problems: 1. Efficiency problem, manual monitoring requires frequent on-site operation, consuming 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 discontinuity of the monitoring process, it is difficult to realize real-time monitoring of the dam body seepage flow, which may cause delay in risk assessment and response measures in emergency situations. In view of the above problems, the existing technology urgently needs an automatic, efficient and accurate seepage flow monitoring method to improve the efficiency and accuracy of monitoring, reduce the risk of manual operation, and realize real-time monitoring of the dam body seepage flow. SUMMARY

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

[0004] The technical solution adopted by the present application is: a dam body seepage flow automatic monitoring method, comprising the following steps:

[0005] The weight data information of the seepage water collected by the weight sensor is sent to the area controller through the acquisition plate;

[0006] The data information is sent to the management system by the area controller, and the data information is stored in the database by the management system;

[0007] The management system calculates the seepage flow access time data, flow data and seepage flow data per unit time according to the transmitted seepage weight data information, and stores the data in the database;

[0008] The management system collects seepage flow data at each time node and pre-processes the collected data;

[0009] The management system performs descriptive statistical analysis on the average, median and standard deviation of seepage flow;

[0010] The management system uses a chart tool to draw a line chart of seepage flow over time;

[0011] The management system performs trend analysis on seepage flow data;

[0012] The management system predicts future changes in seepage flow.

[0013] The collection board is connected to the area controller through the CANbus protocol, and the weight sensor sends the seepage weight data to the area controller through the collection board. The CANbus protocol has error monitoring and arbitration mechanism.

[0014] The area controller is in communication connection with the management system, and the data information storage includes time stamp to record the specific time of each data information.

[0015] The management system calculates the seepage flow access time , flow and seepage flow within one minute according to the transmitted seepage weight data.

[0016] The seepage flow access time is obtained by the following formula:

[0017] ;

[0018] In the formula, is the current time stamp, is the time stamp of the start of monitoring;

[0019] The flow Q is obtained by the following formula:

[0020] ;

[0021] In the formula, represents the seepage weight collected at time stamp ; represents the seepage weight collected at time stamp ; represents the density of water; represents the seepage weight collected at time stamp to time stamp time difference;

[0022] Seepage rate within one minute Obtained by the following formula:

[0023] ;

[0024] Where, Expressed as a unit of time, that is, one minute.

[0025] The preprocessing includes removing outliers, filling missing values, and data standardization.

[0026] The average value M of the seepage rate is obtained by the following formula:

[0027] ;

[0028] Where, is the i-th 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 odd, the median is the middle value; if the number of data points is even, the median is the average of the two middle values.

[0030] The standard deviation S is obtained by the following formula:

[0031] ;

[0032] Where, Represents the seepage data points recorded within a specific time; i represents the total number of observations in the dataset; Represents the total number of observations in the dataset.

[0033] The management system identifies trends in seepage data, including increases, decreases, or cyclical changes, by analyzing charts.

[0034] The management system applies a time series analysis solution and uses a time series forecasting model to predict future changes in seepage volume.

[0035] A dam body seepage flow automatic monitoring system, used to implement the above-mentioned dam body seepage flow automatic monitoring method, comprising:

[0036] A collection module, used to collect water seepage weight data from a water seepage collection device;

[0037] An interactive module, for receiving water seepage weight data and transmitting the data to a management system;

[0038] A storage module, used for storing water seepage weight data;

[0039] an analysis module for converting the water infiltration weight data into volume and analyzing the water infiltration data trends.

[0040] An electronic device comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, the processor performing the steps of the dam seepage flow automated monitoring method.

[0041] The present application has the following beneficial effects:

[0042] The present application integrates a weight sensor, a water infiltration collection device, and a regional controller connected through a CANbus communication protocol, and the regional controller is connected to a management system to realize real-time monitoring of dam seepage conditions. 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 seepage flow and reduces data errors caused by human operation.

[0043] On the other hand, the management system contains descriptive statistical analysis for preliminary sorting and analysis of collected seepage data to identify the basic characteristics and distribution of data, and uses a time series prediction model (ARIMA model) to predict the long-term trend of seepage flow, which helps to identify potential risk points. Through these technical means, management personnel can obtain an understanding of the current seepage conditions and make scientific decisions and plans based on the prediction results, improving the accuracy and intelligence level of dam seepage flow monitoring and providing effective technical support for the safe operation of the dam. BRIEF DESCRIPTION OF DRAWINGS

[0044] In order to more clearly illustrate the specific embodiments of the present application or the technical solutions in the prior art, the following will briefly introduce the drawings needed to be used in the specific embodiments or prior art description. Obviously, the drawings described below are some embodiments of the present application, and those skilled in the art can obtain other drawings according to these drawings without creative labor.

[0045] Figure 1 Flowchart of the automatic monitoring method of the present application.

[0046] Figure 2 Module diagram of the automatic monitoring system of the present application. DETAILED DESCRIPTION

[0047] The technical solutions of the present application will be described clearly and completely below in conjunction with the drawings. Obviously, the described embodiments are part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative labor fall within the scope of protection of the present application.

[0048] Embodiment one:

[0049] Referring to Figure 1 The present application provides a dam seepage flow automatic monitoring method, comprising the following steps:

[0050] S1, sending the seepage weight data information collected by the weight sensor to the area controller through the acquisition board;

[0051] S2, the area controller sends the data information to the management system, and the management system stores the data information in the database;

[0052] S3, the management system calculates the seepage flow time length data, flow data and seepage flow data per unit time according to the transmitted seepage weight data information, and stores the data in the database;

[0053] S4, the management system collects the seepage flow data of each time node and pre-processes the collected data;

[0054] S5, the management system performs descriptive statistical analysis on the average value, median and standard deviation of the seepage flow;

[0055] S6, the management system draws a line chart of seepage flow changing with time by using a chart tool;

[0056] S7, the management system performs trend analysis on the seepage flow data;

[0057] S8, the management system predicts the future change of seepage flow.

[0058] In S1, the seepage collecting device is provided with a weight sensor and an acquisition board, the weight sensor is electrically connected with the acquisition board, the acquisition board is communicatively connected to the area controller, specifically, the acquisition board is connected to the area controller through CANbus protocol, the weight sensor sends the seepage weight data in the seepage collecting device to the area controller through the acquisition board, CANbus protocol supports real-time data communication, ensuring that the acquisition board can quickly transmit the seepage weight data collected by the weight sensor to the area controller, CANbus protocol has error monitoring and arbitration mechanism, which can ensure the accuracy and reliability of data transmission, reducing the risk of data loss or error.

[0059] In S2, the area controller is in communication connection with the management system, the management system receives data from the area controller and stores it in the database, the data storage includes a time stamp to record the specific time of each data record.

[0060] In S3, the management system calculates the duration of the seepage flow according to the transmitted seepage weight data , flow and the seepage flow collected in the collection device within one minute .

[0061] In one of the schemes, the capacity of the seepage collection device is 400 milliliters, when the seepage flow reaches or exceeds 400 milliliters, the time stamp at this time is recorded , the duration is the time difference from the first measurement time stamp to , which is obtained by the following formula:

[0062] ;

[0063] Wherein, is the current time stamp, is the time stamp of the start of monitoring;

[0064] The flow is obtained by the following formula:

[0065]

[0066] Wherein, represents the seepage weight collected as a time stamp ; represents the seepage weight collected as a time stamp ; represents the density of water; represents the time difference from time stamp to time stamp ;

[0067] The seepage flow collected in the collection device within one minute is obtained by the following formula:

[0068] ;

[0069] Wherein, represents the unit time, i.e. one minute.

[0070] The duration , flow and the seepage flow collected in the collection device within one minute The seepage flow data stored in the database is analyzed to predict possible risks and future changes in flow, so as to facilitate the query and analysis of historical data.

[0071] In S4-S5, the management system analyzes the seepage flow change trend by the following steps:

[0072] The management system collects hourly seepage flow data and pre-processes the collected data, including removing outliers, filling missing values, and data standardization;

[0073] The management system performs descriptive statistical analysis on the average, median and standard deviation of seepage;

[0074] The average seepage of the management system M first sums all the seepage data, and then divides the sum by the number of data points to get the average value, which provides the center position of all data points in the data set, and is obtained by the following formula:

[0075] ;

[0076] Where, is the i-th data point, is the total number of data points.

[0077] The median calculation is to arrange the data points in order, if the number of data points is odd, the median is the middle value; if the number of data points is even, 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 central tendency.

[0078] The standard deviation of the management system provides the size of the seepage flow fluctuation, which helps to understand the stability of the seepage and risk assessment, and the standard deviation S is obtained by the following formula:

[0079] ;

[0080] Where, represents the seepage flow data points recorded in a certain time; i represents the total number of observations in the data set; represents the total number of observations in the data set.

[0081] In S6, a line chart of seepage flow over time is drawn using charting tools to visually display trends. The management system extracts seepage flow data and corresponding timestamps from the database and uses Python charting tools to plot these data points in chronological order on the coordinate axes, forming a continuous line, thereby generating a line chart that visually displays the change of seepage flow over time. This chart can be integrated into the management interface, allowing users to interact with it, such as zooming and panning, to view the data trend in detail for a specific time period.

[0082] In S7, the trend of the data is identified by visually inspecting the chart, including rising, falling or periodic changes. Historical data of seepage flow is extracted and preprocessed from the database to ensure the accuracy and integrity of the data, and time series analysis methods are used to identify trend lines and periodic patterns in the data; ARIMA model is used for in-depth analysis of the data to predict future changes in seepage flow.

[0083] In S8, the time series analysis scheme is applied, and the ARIMA model is used to predict future changes in seepage flow. Specifically, historical seepage flow data is extracted from the database, and then used to train the prediction model ARIMA, which is used to predict the change in seepage flow in the future time period.

[0084] The present application integrates a weight sensor, a seepage collection device, and a regional controller connected through a CANbus communication protocol, and the regional controller is connected to a management system to realize real-time monitoring of dam seepage. 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 automatic data collection and processing mechanism improves the efficiency of seepage flow monitoring and reduces data errors caused by human operation.

[0085] On the other hand, the management system includes descriptive statistical analysis for preliminary sorting and analysis of collected seepage data to identify basic characteristics and distribution of data, and uses time series prediction model (ARIMA model) to predict long-term trends of seepage flow, which helps to identify potential risk points. Through these technical means, management personnel can obtain an understanding of the current seepage situation and make scientific decisions and planning based on the prediction results, improving the accuracy and intelligence level of dam seepage flow monitoring and providing effective technical support for safe operation of the dam.

[0086] Embodiment Two:

[0087] Referring to Figure 2 The present application provides a dam seepage flow automatic monitoring system, comprising:

[0088] A collection module for collecting water seepage weight data in the water seepage collection device;

[0089] An interaction module for receiving the water seepage weight data and transmitting the data to a management system;

[0090] A storage module for storing the water seepage weight data;

[0091] An analysis module for converting the water seepage weight data into volume and analyzing the water seepage data trend.

[0092] Embodiment three:

[0093] The 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 steps of a dam seepage flow automatic monitoring method.

[0094] It should be noted that, unless otherwise explicitly stated herein, the execution of these steps does not have strict sequence restrictions, and these steps can be executed in other sequences. Moreover, at least a part of the steps can include multiple steps or multiple stages, which do not necessarily be executed at the same time, but can be executed at different times, and the execution sequence of these steps or stages does not necessarily be sequential, but can be executed in rotation or alternation with other steps or steps or stages in other steps.

[0095] Those skilled in the art should understand that the embodiments of the present application can be provided as a method, a system, or a computer program product. Therefore, the present application can take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present application can take the form of a computer program product implemented on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROMs, optical storage, etc.) containing computer-usable program code.

[0096] The present application is described with reference to flowcharts and / or block diagrams according to the methods, devices (systems), and computer program products of the embodiments of the present application. It should be understood that each flow and / or block in the flowcharts and / or block diagrams, and the combination of the flows and / or blocks in the flowcharts and / or block diagrams can be implemented by computer program instructions. These computer program instructions can be provided to a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing devices to produce a machine, so that the instructions executed by the computer or other programmable data processing devices produce a device that implements the flowcharts and / or block diagrams. Figure 1 one flow or multiple flows and / or blocks Figure 1apparatuses that carry out the functions specified in one or more of the flowcharts or blocks. Figure 1 one or more flowcharts and / or blocks Figure 1 one or more of the flowcharts and / or blocks.

[0097] The computer program instructions can also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the flowcharts and / or blocks Figure 1 one or more flowcharts and / or blocks Figure 1 one or more of the flowcharts and / or blocks.

[0098] The above only is the preferred embodiment of the present application, it should be pointed out that, for those skilled in the technical field, without departing from the technical principles of the present application, can also make several improvements and variations, these improvements and variations should also be considered as the protection scope of the present application.

[0099] The above only is the preferred example of the present application, and does not limit the present application, although the present application is described in detail with reference to the foregoing examples, for those skilled in the art, it still can modify the technical solutions recorded in the foregoing examples, or make equivalent replacement to part of the technical features. Any modification, equivalent replacement, improvement, etc. within the spirit and principles of the present application shall be included in the protection scope of the present application.

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 the database; The management system calculates the seepage flow access duration data, flow data and seepage flow data per unit time based on the transmitted seepage weight data information, and stores the data in the database; The management system collects the seepage data at each time point 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 seepage data; The management system predicts future changes in seepage volume.

2. The method for automatically monitoring dam body seepage according to claim 1, characterized in that: The acquisition board is connected to the regional controller via the CANbus protocol. The weight sensor sends the 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 regional controller is in communication 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 automatically monitoring dam body seepage according to claim 1, characterized in that: The management system calculates the seepage flow 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: ； Where, is the current timestamp, is the timestamp of monitoring start; The flow rate Q is obtained by the following formula: ； Where, 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; Seepage rate within one minute Obtained by the following formula: ； Where, 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 rate is obtained by the following formula: ； Where, is the i-th 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 odd, the median is the middle value; if the number of data points is even, the median is the average of the two middle values. The standard deviation S is obtained by the following formula: ； Where, Represents the seepage data points recorded within a specific time; i represents the total number of observations in the dataset; 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 automatically monitoring 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 the dam body seepage flow automatic monitoring method according to claim 1, characterized in that: include: A collection module, used to collect water seepage weight data from a water seepage collection device; An interactive module, 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 capable of running on the processor, wherein the processor executes the steps of the method for automatically monitoring dam body seepage as claimed in claim 1.

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