Irregular water collecting well equivalent bottom area parameter estimation method, equipment and medium

Abstract

The invention discloses an irregular water-collecting well equivalent bottom area parameter estimation method, equipment and a medium, the method is applied to an F-shaped water-collecting well, and comprises the following steps: collecting real-time water level data of two water-collecting wells, carrying out data processing and synchronization, and generating a water level data set with synchronous timestamps; setting a sliding window, calculating a water level change rate, and detecting a current water level stage; recording timestamps corresponding to the lowest water level value and the highest water level value of each period; the water level difference and the time difference from the lowest water level to the preset threshold water level and from the preset threshold water level to the highest water level in the current period of the two water collecting wells are obtained through calculation; calculating a base area estimated value of the current period; and constructing a Kalman filtering model, initializing parameters, inputting the base area estimated value into the model for iterative updating, and outputting a current estimated value. According to the method, the equivalent bottom area of the inverted-F-shaped water collecting well is estimated, and the precision of an output result is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of safety monitoring of hydropower stations, and particularly relates to a method, device and medium for estimating the equivalent bottom area parameter of an irregular sump. Background Art

[0002] In the field of operation and maintenance of hydropower stations, the overhaul drainage sump and the leakage sump of the underground cavern powerhouse are key facilities for monitoring the leakage water volume of the powerhouse. The incoming water volume data directly reflects the dynamic trend of seepage water, and is an important monitoring index for preventing the powerhouse from being flooded.

[0003] Currently, in this field, the incoming water volume is generally calculated by combining the water level change value of the sump with the equivalent volume, and the core parameter is the equivalent bottom area of the sump. However, based on the existing monitoring and calculation methods, when facing a sump with an irregular structure, parameter distortion will occur. For example, when the sump is in an inverted "F" shape or a complex irregular shape, due to the deviation between the actual construction effect and the design drawing (such as the corner radian, partition wall inclination, etc.), and the accumulation of dirt in the water collection corridor during long-term operation, the obtained equivalent bottom area data of the sump is inaccurate, thus affecting the calculation accuracy of the incoming water volume value of the sump and causing certain interference to the monitoring of the safe and stable operation of the power station. Summary of the Invention

[0004] To solve the above problems, the present invention provides a method for estimating the equivalent bottom area parameter of an irregular sump, which is applied to a sump in the shape of an F body, and the specific technical solution is as follows:

[0005] S1: Collect the real-time water level data of the first target sump and the second target sump, perform data processing and synchronization to generate a water level data set with a synchronized timestamp;

[0006] S2: Set a sliding window, calculate the water level change rate based on the water level data set, and detect the current water level stage;

[0007] S3: Record the timestamps corresponding to the lowest water level value and the highest water level value in each cycle;

[0008] S4: Calculate and obtain the water level difference h 1_d 、h 2_d from the lowest water level of the current cycle of the two sumps to the preset threshold water level, and the time difference t1;

[0009] S5: Calculate and obtain the water level difference h 1_g 、h 2_g from the preset threshold water level to the highest water level of the current cycle of the two sumps, and the time difference t2;

[0010] S6: Calculate the bottom area estimation value of the current cycle;

[0011] S7: Construct a Kalman filter model, initialize the parameters, input the estimated bottom area value into the model for iterative update, and output the current estimated value.

[0012] Further, in step S1, the data processing and synchronization are as follows:

[0013] Align the timestamps of the real-time water level data collected from the two sump wells through linear interpolation method to fill in the missing data points;

[0014] Set a time tolerance threshold, and perform piecewise interpolation on the abnormal data segments that exceed the time tolerance threshold.

[0015] Further, in step S2, the specific process of water level stage detection is as follows:

[0016] According to the set sliding window, calculate the average water level change rate within the window;

[0017] If the average change rate is greater than the positive threshold for M consecutive times, the current water level stage is the rising stage; if the change rate is less than the negative threshold for M consecutive times, the current water level stage is the falling stage.

[0018] Further, in step S3, according to the average change rate calculated by sliding in step S2, when the average water level change rate changes from negative to positive, record the current water levels L1 and L2 as the lowest water level values corresponding to the two sump wells, and the corresponding timestamp is recorded as t L ;

[0019] When the average water level change rate changes from positive to negative, record the current water levels as H1 and H2 as the highest water level values corresponding to the two sump wells, and the corresponding timestamp is t H .

[0020] Further, in step S3, there is also a continuous number K. When the positive and negative of the average change rate change, and the changed positive or negative value is satisfied in the sliding calculation results of K consecutive times, then record the current water level value and timestamp.

[0021] Further, in step S4, the specific process of obtaining the water level difference and time difference from the current cycle lowest water level to the preset threshold water level of the two sump wells is as follows:

[0022] When the water levels of the two sump wells continuously exceed the preset threshold water level Q for P times during the rising stage, record the trigger time t Q ;

[0023] For the first target sump well, the water level difference h from the current cycle lowest water level to the preset threshold water level 1_d = Q - L1;

[0024] For the second target sump well, the water level difference h from the current cycle lowest water level to the preset threshold water level2_d = Q - L2;

[0025] The time difference t1 = t Q - t L .

[0026] Further, in step S6, the estimated bottom area of the current cycle is calculated as follows:

[0027]

[0028] where y obs represents the estimated bottom area of the current cycle, and s1 and s2 respectively represent the bottom areas of the cubic segments of the first target sump and the second target sump.

[0029] The present invention also provides a device for estimating the equivalent bottom area parameters of an irregular sump, including: a memory, a processor, and an irregular sump equivalent bottom area parameter estimation program stored on the memory and executable on the processor. When the irregular sump equivalent bottom area parameter estimation program is executed by the processor, the steps of the above-mentioned irregular sump equivalent bottom area parameter estimation method are implemented.

[0030] The present invention also provides a computer storage medium, on which an irregular sump equivalent bottom area parameter estimation program is stored. When the irregular sump equivalent bottom area parameter estimation program is executed by a processor, the steps of the above-mentioned irregular sump equivalent bottom area parameter estimation method are implemented.

[0031] The beneficial effects of the present invention are as follows:

[0032] The present invention synchronizes data by collecting real-time water level data of two sumps through sensors, detects the water level stage, performs cycle segmentation and Q-value triggering, and combines Kalman filtering to dynamically optimize the observed values, realizing the estimation of the equivalent bottom area of the inverted "F"-shaped sump. Moreover, the estimation result can infinitely approach the real data as the amount of calculation set data input increases, thereby providing high-precision parameters for the subsequent calculation of the water inflow of the sump. Description of the Drawings

[0033] Figure 1 is a schematic flowchart of the method of the present invention. Detailed Embodiments

[0034] In the following description, the technical solutions in the embodiments of the present invention are clearly and completely described. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts fall within the protection scope of the present invention.

[0035] In the description of the embodiments of the present invention, it should be noted that the indicated orientation or positional relationship is based on the orientation or positional relationship shown in the drawings, or the orientation or positional relationship in which the inventive product is customarily placed during use, or the orientation or positional relationship commonly understood by those skilled in the art, or the orientation or positional relationship in which the inventive product is customarily placed during use. It is only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore should not be construed as a limitation to the present invention. In addition, the terms "first" and "second" are only used for differential description and should not be construed as indicating or implying relative importance.

[0036] In the description of the embodiments of the present invention, it should also be noted that unless otherwise clearly specified and defined, the terms "set" and "connect" should be understood in a broad sense. For example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a direct connection or an indirect connection through an intermediate medium. For those of ordinary skill in the art, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0037] Embodiment 1

[0038] Embodiment 1 of the present invention discloses a method for estimating the equivalent bottom area parameter of an irregular sump, which is applied to the sump of the F-shaped body, as Figure 1 shown, specifically as follows:

[0039] S1: The water level data of the first target sump and the second target sump are collected in real time through a water level sensor, and data processing and synchronization are performed to align the time series data of the two sensors, and a water level data set with synchronized timestamps is generated;

[0040] As a preferred embodiment, the data processing and synchronization are specifically as follows:

[0041] The timestamps of the real-time water level data collected from the two sumps are aligned by the linear interpolation method to fill in the missing data points;

[0042] A time tolerance threshold is set, and segmented interpolation is performed on the abnormal data segments exceeding the time tolerance threshold.

[0043] S2: A sliding window is set, and the water level change rate is calculated based on the water level data set to detect the current water level stage;

[0044] In this embodiment, the length of the sliding window is N sampling points (N≥3);

[0045] Specifically, according to the set sliding window, the average water level change rate within the window is calculated;

[0046] If the average rate of change is greater than the positive threshold for M consecutive times, the current water level stage is the rising stage. If the rate of change is less than the negative threshold for M consecutive times, the current water level stage is the falling stage;

[0047] where M ≥ 2.

[0048] S3: Record the timestamps corresponding to the lowest water level value and the highest water level value in each cycle;

[0049] In this embodiment, according to the average rate of change obtained by sliding calculation in step S2, when the average water level rate of change changes from negative to positive, record the current water levels L1 and L2 as the lowest water level values corresponding to the two sump wells, and the corresponding timestamp is recorded as t L ;

[0050] When the average water level rate of change changes from positive to negative, record the current water levels as H1 and H2 as the highest water level values corresponding to the two sump wells, and the corresponding timestamp is t H 。

[0051] As a preferred embodiment, in step S3, there is also a continuous number K. When the positive or negative of the average rate of change changes, and it satisfies the changed positive or negative value in the sliding calculation results of K consecutive times, then record the current water level value and the timestamp.

[0052] S4: Calculate and obtain the water level difference h 1_d 、h 2_d and the time difference t1 between the lowest water level of the current cycle of the two sump wells and the preset threshold water level;

[0053] The specific process is as follows:

[0054] When the water levels of the two sump wells continuously exceed the preset threshold water level Q for P times during the rising stage, record the trigger time t Q ;

[0055] For the first target sump well, the water level difference h 1_d = Q - L1;

[0056] For the second target sump well, the water level difference h 2_d = Q - L2;

[0057] The time difference t1 = t Q - t L 。

[0058] S5: Calculate and obtain the water level difference h 1_g 、h 2_g and the time difference t2 between the preset threshold water level and the highest water level of the current cycle of the two sump wells;

[0059] For the first target sump, the water level difference h from the preset threshold water level to the highest water level in the current cycle 1_g = H1 - Q;

[0060] For the second target sump, the water level difference h from the preset threshold water level to the highest water level in the current cycle 2_g = H2 - Q;

[0061] The time difference t2 = t H - t Q .

[0062] S6: Calculate the estimated bottom area in the current cycle;

[0063] Specifically, the calculation is as follows:

[0064]

[0065] where y obs represents the estimated bottom area in the current cycle, and s1 and s2 represent the bottom areas of the cubic segments of the first target sump and the second target sump respectively.

[0066] S7: Construct a Kalman filter model, initialize the parameters, and input the estimated bottom area into the model for iterative update;

[0067] Specifically, for the Kalman filter model, the state equation is defined as y k = y k-1 , and the observation equation is defined as z k = y k + v k , where y is the fixed value to be estimated, and v k is the observation noise obeying the Gaussian distribution;

[0068] Set the initial estimated value as the first observation value or zero, the initial covariance P0 is a preset large value, the process noise variance Q = 0, and the observation noise variance R is a preset initial value;

[0069] Specifically, the observation noise variance R is adaptively adjusted dynamically:

[0070]

[0071] where α is the learning rate, and the value range is 0 < α < 1.

[0072] Specifically, the iterative update is performed based on the following process;

[0073] S701: Prediction, the calculation is as follows:

[0074]

[0075] Calculate the Kalman gain:

[0076]

[0077] Update the estimate:

[0078]

[0079] Update the covariance:

[0080]

[0081] As a preferred embodiment, when the observation residual exceeds a preset threshold δ, perform the following operations:

[0082] Skip the current observation value z k Or temporarily increase the observation noise variance R to R' = βR, where β > 1.

[0083] Output the current estimate Until the covariance P k converges to a preset threshold.

[0084] Embodiment 2

[0085] Embodiment 2 of the present invention discloses a non-regular sump equivalent bottom area parameter estimation device. The device may be a user equipment (UE) such as a mobile phone, a smart phone, a laptop computer, a digital broadcast receiver, a personal digital assistant (PDA), a tablet computer (PAD), a handheld device, a vehicle-mounted device, a wearable device, a computing device, or other processing devices connected to a wireless modem, a mobile station (MS), etc. The device may be referred to as a user terminal, a portable terminal, a desktop terminal, etc.

[0086] Generally, the device includes: at least one processor, a memory, and a non-regular sump equivalent bottom area parameter estimation program stored on the memory and executable on the processor. The non-regular sump equivalent bottom area parameter estimation program is configured to implement the steps of the non-regular sump equivalent bottom area parameter estimation method as described in Embodiment 1.

[0087] The processor may include one or more processing cores, such as a 4-core processor, an 8-core processor, etc. The processor may be implemented in at least one of the following hardware forms: DSP (Digital Signal Processing), FPGA (Field-Programmable Gate Array), and PLA (Programmable Logic Array). The processor may also include a main processor and a coprocessor. The main processor is used to process data in the wake state and is also called the CPU (Central Processing Unit); the coprocessor is a low-power processor used to process data in the standby state. In some embodiments, the processor may be integrated with a GPU (Graphics Processing Unit), and the GPU is responsible for rendering and drawing the content to be displayed on the display screen. The processor may also include an AI (Artificial Intelligence) processor, which is used to process the calculation operations related to the non-regular sump equivalent bottom area parameter estimation program, enabling the non-regular sump equivalent bottom area parameter estimation method to autonomously train and learn, improving efficiency and accuracy.

[0088] The memory may include one or more computer-readable storage media, and the computer-readable storage media may be non-transitory. The memory may also include high-speed random access memory and non-volatile memory, such as one or more disk storage devices and flash storage devices. In some embodiments, the non-transitory computer-readable storage media in the memory is used to store at least one instruction, and the at least one instruction is used to be executed by the processor to implement the non-regular sump equivalent bottom area parameter estimation method described in Embodiment 1.

[0089] In some embodiments, the terminal may optionally further include: a communication interface and at least one peripheral device. The processor, the memory, and the communication interface may be connected through a bus or signal lines. Each peripheral device may be connected to the communication interface through a bus, signal lines, or a circuit board. Specifically, the peripheral device includes at least one of the following: a radio frequency circuit, a display screen, and a power supply.

[0090] The communication interface can be used to connect at least one peripheral device related to I / O (Input / Output) to the processor and the memory. The communication interface is used by the peripheral device to receive the movement trajectories and other data of multiple mobile terminals uploaded by the user. In some embodiments, the processor, the memory, and the communication interface are integrated on the same chip or circuit board; in some other embodiments, any one or two of the processor, the memory, and the communication interface can be implemented on a separate chip or circuit board, and this embodiment does not limit this.

[0091] The radio frequency circuit is used to receive and transmit RF (Radio Frequency) signals, also known as electromagnetic signals. The radio frequency circuit communicates with the communication network and other communication devices through electromagnetic signals, so as to obtain the movement trajectories and other data of multiple mobile terminals. The radio frequency circuit converts the electrical signal into an electromagnetic signal for transmission, or converts the received electromagnetic signal into an electrical signal. Optionally, the radio frequency circuit includes: an antenna system, an RF transceiver, one or more amplifiers, a tuner, an oscillator, a digital signal processor, a codec chipset, a user identity module card, and so on. The radio frequency circuit can communicate with other terminals through at least one wireless communication protocol. The wireless communication protocol includes but is not limited to: metropolitan area network, each generation of mobile communication network (2G, 3G, 4G, and 5G), wireless local area network, and / or WiFi (Wireless Fidelity) network. In some embodiments, the radio frequency circuit may also include a circuit related to NFC (Near Field Communication), which is not limited here.

[0092] The display screen is used to display the UI (User Interface). The UI may include graphics, text, icons, videos, and any combination thereof. When the display screen is a touch display screen, the display screen also has the ability to collect touch signals on or above the surface of the display screen. The touch signal can be input to the processor as a control signal for processing. At this time, the display screen can also be used to provide virtual buttons and / or a virtual keyboard, also known as soft buttons and / or a soft keyboard. In some embodiments, the display screen can be one, the front panel of the electronic device; in some other embodiments, the display screen can be at least two, respectively arranged on different surfaces of the electronic device or in a folding design; in still some other embodiments, the display screen can be a flexible display screen, arranged on the curved surface or the folding surface of the electronic device. Even, the display screen can be set to an irregular non-rectangular shape, that is, a special-shaped screen. The display screen can be prepared from materials such as LCD (Liquid Crystal Display) and OLED (Organic Light-Emitting Diode).

[0093] The power supply is used to supply power to each component in the electronic device. The power supply can be alternating current, direct current, a disposable battery, or a rechargeable battery. When the power supply includes a rechargeable battery, the rechargeable battery can support wired charging or wireless charging. The rechargeable battery can also be used to support fast charging technology.

[0094] Embodiment 3

[0095] Embodiment 3 of the present invention discloses a computer storage medium. The storage medium is a readable storage medium storing a computer program. When the computer program is executed by a processor, the steps of the method for estimating the equivalent bottom area parameter of the non-regular sump in Embodiment 1 are implemented.

[0096] Specifically, the readable storage medium can be various readable storage media such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disc, etc., which can store program codes.

[0097] The present invention is not limited to the foregoing specific embodiments. The present invention extends to any new feature or any new combination disclosed in this specification, as well as any new combination of the steps of any new method or process disclosed.

Claims

1. A method for estimating the equivalent bottom area parameter of an irregular sump, characterized in that A sump applied to an F-shaped body, the method includes: S1: Collect the real-time water level data of the first target sump and the second target sump, perform data processing and synchronization, and generate a water level data set with a synchronized timestamp; S2: Set a sliding window, calculate the water level change rate based on the water level data set, and detect the current water level stage; S3: Record the timestamps corresponding to the lowest water level value and the highest water level value in each cycle; S4: Calculate and obtain the water level difference h between the lowest water levels of the two sump wells in the current cycle and the preset threshold water level 1_d 、h 2_d and the time difference t1; S5: Calculate and obtain the water level difference h between the preset threshold water level and the highest water level of the two sump wells in the current period 1_g , h 2_g and the time difference t2; S6: Calculate the bottom area estimation value of the current cycle; S7: Construct a Kalman filter model, initialize the parameters, input the bottom area estimation value into the model for iterative update, and output the current estimation value.

2. The method for estimating the equivalent bottom area parameter of an irregular sump according to claim 1, wherein In step S1, the data processing and synchronization are as follows: Align the timestamps of the real-time water level data collected from the two sumps by linear interpolation method to fill in the missing data points; Set a time tolerance threshold, and perform piecewise interpolation on the abnormal data segments exceeding the time tolerance threshold.

3. The method for estimating the equivalent bottom area parameter of the irregular sump according to claim 1, characterized in that In step S2, the specific process of water level stage detection is as follows: According to the set sliding window, calculate the average water level change rate within the window; If the average change rate is greater than the positive threshold for M consecutive times, the current water level stage is the rising stage; if the change rate is less than the negative threshold for M consecutive times, the current water level stage is the falling stage.

4. The method for estimating the equivalent bottom area parameter of an irregular sump according to claim 3, wherein, In step S3, according to the average change rate obtained by sliding calculation in step S2, when the average water level change rate changes from negative to positive, record the current water levels L1 and L2 as the lowest water level values corresponding to the two sump wells, and the corresponding time stamp is recorded as t L ; When the average water level change rate changes from positive to negative, record the current water level as H1, H2 as the highest water level values corresponding to the two sumps, and the corresponding timestamp as t H 。 5. The method for estimating the equivalent bottom area parameter of an irregular sump according to claim 4, wherein In step S3, there is also a continuous number K. When the positive and negative of the average change rate change, and the changed positive or negative value is satisfied in the continuous K sliding calculation results, the current water level value and timestamp are recorded.

6. The method for estimating the equivalent bottom area parameter of an irregular sump according to any one of claims 4-5, characterized in that In step S4, the specific process of obtaining the water level difference and time difference from the lowest water level to the preset threshold water level in the current cycle of the two sumps is as follows: When the water levels of two sump wells continuously exceed the preset threshold water level Q for P times during the rising stage, record the trigger time t Q ; For the first target sump, the water level difference h between the lowest water level in the current cycle and the preset threshold water level 1_d = Q - L1; The water level difference h between the lowest water level in the current cycle and the preset threshold water level of the second target sump 2d = Q - L2; The time difference t1 = t Q -t L .

7. The method for estimating the equivalent bottom area parameter of an irregular sump according to claim 6, wherein In step S6, the bottom area estimation value of the current cycle is calculated as follows: Among them, y obs represents the estimated value of the bottom area in the current period, and s1 and s2 respectively represent the bottom areas of the cubic segments of the first target sump and the second target sump.

8. An irregular sump equivalent bottom area parameter estimation device, characterized in that The non-regular sump equivalent bottom area parameter estimation device includes: a memory, a processor, and a non-regular sump equivalent bottom area parameter estimation program stored on the memory and executable on the processor. When the non-regular sump equivalent bottom area parameter estimation program is executed by the processor, it implements the steps of the non-regular sump equivalent bottom area parameter estimation method according to any one of claims 1-7.

9. A computer storage medium, characterized in that, The non-regular sump equivalent bottom area parameter estimation program is stored on the storage medium. When the non-regular sump equivalent bottom area parameter estimation program is executed by the processor, it implements the steps of the non-regular sump equivalent bottom area parameter estimation method according to any one of claims 1-7.

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