Redundant measurement value transmitting method of ship lock chamber single-point water level gauge

Abstract

The application discloses a redundant measurement value transmitting method for a single measuring point water level gauge of a ship lock chamber. The method comprises the following steps: simultaneously detecting the water level of a certain measuring point in the ship lock chamber by N water level gauges, obtaining multiple water level detection values of the measuring point at a certain time; determining a water level deviation threshold G2 of the measuring point and a detection value deviation threshold G3 of the multiple water level gauges according to a ship lock chamber water level change threshold G1 and a water level gauge detection range R; comparing the multiple water level detection values Vn of a certain measuring point with the determined water level deviation threshold G2 of the measuring point; performing difference value operation on the obtained reasonable water level detection value Vm; selecting N1 water level detection values as the water level detection basic data of the measuring point, performing secondary processing, and obtaining the water level detection effective value Ve of the measuring point. The application discloses a redundant measurement value transmitting method for a single measuring point water level gauge of a ship lock chamber. The ship lock single measuring point adopts multiple water level sensors for redundant detection, voting verification, error processing and detection value transmission of multiple detection values, and reliable and stable water level data is provided for the system.

Description

Technical Field

[0001] This invention relates to the field of lock chamber water level detection technology, specifically to a method for transmitting redundant measurement values ​​of a single-point water level gauge in a lock chamber. Background Technology

[0002] High reliability of pressure sensors is one of the guarantees for the safe operation of ship lock control systems. Both the Three Gorges Dam and Gezhouba Dam ship locks use Drucker piezoelectric level sensors for water level detection, employing a multi-point redundancy method to detect water level signals, which are directly input into the central PLC control system for processing. The accuracy requirements for water level detection vary at different stages of ship lock operation. According to the design specifications for ship locks, the forward head should not exceed 0.01 meters, and the reverse head should not exceed 0.02 meters (the document requires the horizontal signal to maintain a head of -12.5cm to +5cm). Currently, the water level detection system of the Three Gorges Dam ship lock does not meet this technical requirement. Water level sensors that meet this technical requirement are currently rare on the market, and the Drucker PTX1830 currently used is expensive, prone to failure, and is not a domestically produced product.

[0003] The reliability and stability of the water level signal in a lock chamber are crucial for the normal operation of the lock. For multi-stage or single-stage locks, water level detection involves multiple points. The reliability and stability of the water level signal at each detection point directly affects the stability and reliability of the entire lock's water level detection system. Therefore, research on single-point water level detection methods for locks can effectively ensure the reliability and stability of the lock's water level detection system. Water level detection in high-head locks is the most important pressure signal detection related to the safety of the lock's operation. It has a direct control relationship with important operational nodes such as valve operation and gate horizontal opening, and is a fundamental aspect of the lock's healthy operation.

[0004] The water level detection of a lock chamber is based on placing water level detection sensors at one or more locations upstream, midstream, or downstream of the lock chamber. The lock chamber area is regarded as an independent detection point, and the water level of the lock chamber is obtained by comprehensively processing the water level values ​​detected at multiple single locations. For a single detection location within the lock chamber, the reliability and accuracy of the water level detection at that single detection point determines the reliability and accuracy of the water level detection of the entire lock chamber.

[0005] The water level detection of a ship lock chamber is based on the comprehensive results of multiple single measuring points within the chamber. However, current methods for detecting water level at single measuring points in ship lock chambers have the following problems:

[0006] 1) Since there is only one water level gauge at a single point, the single-point water level detection lacks reliability and comparability. If two water level gauges in the same lock chamber fail at the same time or detect large fluctuations, the control system will be unable to generate a horizontal signal, resulting in the interruption of lock operation.

[0007] 2) Currently, the reliability of water level information relies on the reliability of individual water level gauges. Once the water level gauge readings drift, the reliability of the entire system rapidly declines, and safety risks increase simultaneously. Therefore, the verification function of water level gauge readings is a fundamental requirement for the reliability control of water level gauges.

[0008] 3) The water level detection at a single measuring point lacks self-diagnostic functions such as judgment, verification, and correction. The water level detection at a single measuring point lacks judgment and verification of reliability and accuracy, which directly affects the reliability and stability of water level detection in the gate chamber.

[0009] 4) The sensor detection signals from multiple single measurement points lack primary and secondary processing. The detection signals are directly aggregated in the core CPU control system for signal processing, which increases the computing power burden on the core control system of the lock. Summary of the Invention

[0010] To ensure the accuracy and reliability of water level detection in lock chambers, and to reduce the computational burden of voting verification calculations for redundant measurements from distributed pressure sensors, this invention provides a method for transmitting redundant measurements from a single measuring point in a lock chamber. In this method, multiple water level sensors are used for redundant detection at a single measuring point in the lock, and voting verification, error processing, and transmission of multiple measurements are performed to provide the system with reliable and stable water level data.

[0011] The technical solution adopted in this invention is as follows:

[0012] The method for transmitting redundant measurement values ​​of a single-point water level gauge in a lock chamber includes the following steps:

[0013] Step 1: Simultaneously detect the water level at a certain detection point in the lock chamber using N water level gauges, and obtain multiple water level detection values ​​at that detection point at a certain moment, Vn, n=1,2,...,N;

[0014] Step 2: Based on the lock chamber water level change threshold G1 and the water level gauge detection range R, determine the water level deviation threshold G2 and the detection value deviation threshold G3 of the multiple water level gauges at the detection point.

[0015] Step 3: Compare the multiple water level gauge readings Vn at a certain detection point in Step 1 with the water level deviation threshold G2 determined in Step 2 for that detection point. Water level readings exceeding the water level deviation threshold G2 are discarded and do not participate in the next data processing step; the remaining M water level readings are reasonable values ​​Vm, m = 1, 2, ..., M, and participate in the next data processing step.

[0016] Step 4: Perform a difference calculation on the reasonable water level detection value Vm obtained in Step 3. If the deviation between a certain water level detection value and the other two water level detection values ​​exceeds the deviation threshold determined in Step 2, then the water level detection value is eliminated and will not participate in the next data processing step; at the same time, the water level gauge corresponding to the water level detection value is cut off.

[0017] Step 5: The N1 water level detection values ​​Vi, i = 1, 2, ..., N1 after step 4 are used as the basic data for water level detection at this detection point. They are then processed to obtain the effective water level detection value Ve at this detection point.

[0018] Step Six: Output the effective value of water level detection, Ve, from Step Five after standard electrical signal processing.

[0019] In step two:

[0020] The water level change threshold G1 of a certain gate chamber refers to the maximum difference between the lowest and highest water levels in that gate chamber.

[0021] The water level gauge's detection range R refers to the maximum water level change that the water level sensor can measure. If the water level change threshold G1 is 35 meters, a water level sensor with a range R of 40 meters can be used to measure the water level in the gate chamber.

[0022] The water level deviation threshold G2 includes a dynamic water level deviation threshold and a static water level deviation threshold. The dynamic water level deviation threshold refers to the maximum limit of water level change per minute under filling and releasing conditions. Assuming the maximum limit of water level change during filling and releasing of the gate chamber is 1 meter / minute, then under this dynamic condition, the absolute value of the change in the measured value corresponding to the water level gauge per minute should not exceed 1 meter. The static water level deviation threshold refers to the absolute value of water level change per minute at the detection point under conditions without filling and releasing conditions.

[0023] The detection deviation threshold G3 refers to the maximum deviation limit between the detection values ​​of multiple sensors at the same detection point at the same time. This value reflects the concentration between the detection values ​​of redundant sensors at a single measuring point and can be used to judge the reliability of water level detection at a single measuring point. For example, if the detection deviation threshold of multiple water level gauges is set to 0.4 meters, then if the deviation between any two water level detection values ​​is greater than 0.4 meters, it can be determined that the performance of one of the sensors has deteriorated.

[0024] In step four, the difference calculation refers to subtracting the average of multiple water level detection values ​​from a single water level detection value. In step four, a reasonable water level detection value refers to a water level detection value Vm, where m = 1, 2, ..., M, and M ≤ N, within the deviation range. Assuming the deviation threshold is set to 0.4 meters, and the deviation between water level detection values ​​V1 and V2 is 0.5 meters, and the deviation between V1 and V3 is 0.6 meters, both exceeding the deviation threshold, it can be determined that the sensor performance of water level detection value V1 has deteriorated, and this water level detection value and its corresponding water level gauge should be discarded.

[0025] The secondary processing in step five includes the following steps:

[0026] S5.1 Error Analysis:

[0027] The data processing model for water level detection was established based on factors such as the water level gauge detection environment, water level gauge installation method, and water level fluctuation in the gate chamber.

[0028] The temperature, humidity, and air pressure of the environment in which a water level gauge is detected can affect its measurement accuracy. Therefore, when analyzing water level detection data, it is necessary to consider the influence of the detection environment and to correct and adjust the data to eliminate the influence of environmental factors.

[0029] In water level gauge testing environments, a blank test error method can be used. Before installing the water level gauge, appropriate initial environmental parameters are set. If the actual environmental reading is higher or lower than the initial environmental reading, an appropriate calibration coefficient is selected to calibrate the water level gauge's measurement to the parameters of the current environment. This serves as a comparison, effectively controlling system errors.

[0030] The installation method of a water level gauge can also affect water level detection data. For example, parameters such as the installation location, height, and angle of the gauge can affect its measurement accuracy and sensitivity. Therefore, when analyzing water level detection data, it is necessary to consider the impact of the installation method and correct and adjust the data to eliminate the influence of installation factors.

[0031] For water level gauge installation, the following steps can be followed:

[0032] (1) Check the installation position and orientation of the water level gauge, such as the installation height and angle; avoid errors caused by vibration or movement, and ensure that the water level gauge is placed in a horizontal position;

[0033] (2) Correcting zero-point error: Zero-point error refers to the situation where the reading is not zero when the water level gauge is in a horizontal position within its measurement range. When the water level gauge is in a horizontal position, adjust the zero-point offset to make the reading zero.

[0034] (3) Proportional error correction: Proportional error refers to the difference between the reading and the actual water level when the water level gauge is in a horizontal position within its measurement range. Proportional error can be corrected by calibrating the water level gauge at a known water level. If the reading is too high or too low, the proportional error can be corrected by adjusting the coefficient of the water level gauge.

[0035] The fluctuation of water level in the lock chamber can be verified by using mathematical and physical models. Considering the influence of water flow inertia during lock filling and emptying, a two-dimensional unsteady flow mathematical model of lock chamber water surface fluctuation and a one-dimensional mathematical model of lock filling and emptying water are used to solve the model.

[0036] The fundamental equations for the planar two-dimensional unsteady water flow motion, including the second-order turbulent peak, are as follows:

[0037] Continuity equation

[0038] equations of motion

[0039]

[0040] Where ζ is the water level, d is the water depth, H = ζ + d is the total water depth, u is the x-axis velocity, v is the y-axis velocity, and ρ is the density of water. For the bottom stress in the x-direction, The stress is at the bottom in the y-direction. Here, n is the Chezy coefficient, and n is the Manning roughness coefficient. L is the turbulent viscosity coefficient. m =0.1H is the mixing length.

[0041] The basic hydraulic equations considering inertial effects and the lock filling and emptying process are as follows:

[0042]

[0043] Equation of water level change in the sluice chamber

[0044]

[0045] Where: H is the water level of the approach channel, Z is the water level of the lock chamber, V is the average flow velocity of the calculated cross-section of the corridor, μ is the flow coefficient, and L is the average flow velocity of the channel. m ω is the converted length of the water conveyance corridor, ω is the calculated cross-sectional area of ​​the water conveyance corridor, and Ω is the water surface area of ​​the gate chamber.

[0046] S5.2 Data Fusion Processing:

[0047] Step four involves pre-processing the water level readings and performing comprehensive calculations, as detailed below:

[0048] Using multi-sensor data fusion technology, the Kalman filter is first applied to the water level detection data from the sensors, and the noise covariance matrix is ​​measured. Then, a fuzzy evaluation of the reliability of the sub-filters is performed, and the ratio η of the actual to the theoretical value of the filter innovation divergence is selected. i (k) and the trace tr(p) of the state estimation error covariance. i (k) is used as a fuzzy evaluation parameter for the credibility of sub-filters to establish a fuzzy evaluation of filter credibility;

[0049] Select the parameters and perform the following transformation: p Fi (k)=|tr(p i (k))|,CE I (k)=|η i(k)-1|, which are used as the input values ​​of the fuzzy observer. The fuzzy subset of the input is defined as: {Z(zero), SE(small), S(small), B(large), BE(large)}, and the universe of discourse is chosen to be [0, 1].

[0050] The output ζ of the fuzzy observer i (k) represents the confidence level of each filter, with its universe of discourse being [0, 1]. Its fuzzy subset is defined as: {VL (lower), L (lower), M (medium), H (higher), VH (higher)}.

[0051] Calculate the weighting factors:

[0052]

[0053] N represents the number of sensors in the fusion system.

[0054] The weighting coefficients and the estimated state values ​​X of each sub-filter i (k) derives the global estimate X(k) and outputs the comprehensive calculation result.

[0055]

[0056] In step five, the values ​​after secondary processing are further processed to obtain the effective water level detection value, as shown in the following formula:

[0057]

[0058] Among them, V RMS V represents the valid value of the water level detection, V(i) represents the i-th data point sampled, and N represents the number of data points sampled.

[0059] The effective value of water level detection refers to the valid value representing the water level height obtained by calculating the water pressure signal. The effective value is an averaged value obtained during the signal's change process, resulting in a value with the same power as the original signal, and thus more accurately reflects the signal strength.

[0060] In step six, the standard electrical signal processing includes A / D conversion, D / A conversion, and signal amplification, outputting a 4-20mA electrical signal. The output signal interface and signal format meet the actual requirements for water level detection in the lock chamber. Specifically, the output signal interface has four channels for analog and digital outputs, and the transmitted signal uses a 4-20mA signal format.

[0061] This invention provides a method for transmitting redundant measurement values ​​from a single-point water level gauge in a ship lock chamber, with the following technical advantages:

[0062] 1) In step one of this invention, using multiple water level gauges for simultaneous detection can reduce the error of a single water level gauge, improve detection accuracy, and avoid the problem of inaccurate water levels when ships enter or leave due to the error of a single water level gauge; it can improve the reliability of detection, even if one water level gauge fails, the other water level gauges can still continue to work, ensuring the continuity and reliability of detection; it can distribute the tasks of maintenance and upkeep to multiple water level gauges, reducing the workload of a single water level gauge, and also making it easier to replace and repair water level gauges that have problems, thus improving the maintainability and reliability of the equipment.

[0063] 2) In step two of this invention, by determining the deviation range and deviation threshold, the reliability of water level control can be improved, maintenance personnel can easily maintain and manage the water level detection equipment, and equipment faults and abnormalities can be detected in advance. The reliability of the water level gauge probe and whether the sensor performance has deteriorated can be preliminarily judged, thereby reducing the time and cost of maintenance and repair.

[0064] 3) Steps three and four of this invention, using the deviation range and deviation threshold determined in step two to obtain reasonable water level detection values, can simplify data processing, reduce processing complexity, and improve processing efficiency. They can also reduce the amount of data stored and transmitted, thus lowering costs. Furthermore, they can improve the reliability of data analysis, avoiding inaccurate analysis results due to erroneous data, thereby enhancing the reliability and accuracy of data analysis. Finally, they can ensure the stability of water level control, avoiding improper water level control due to erroneous data, thereby improving the safety and stability of water level control.

[0065] 4) In step five of this invention, secondary data processing can convert the data into a more user-friendly format, such as visualization, statistics, and analysis, thereby improving data usability and facilitating data processing and decision-making; by performing error analysis on the data, the sources of error in the data can be identified, and the data can be corrected and compensated, thereby improving the accuracy and precision of the data; through data fusion processing, data from different sources and of different types can be merged, improving the reliability and accuracy of the data, and avoiding the problems of incomplete or inaccurate data caused by a single data source or a single data type.

[0066] 5) This invention uses a majority vote to initially screen the water level gauge readings, judge the reliability and stability of the water level gauge, and obtains and outputs the final water level reading of a certain measuring point in the lock chamber through secondary calculation of the basic data, thus ensuring the accuracy and effectiveness of the water level reading at that measuring point. Attached Figure Description

[0067] The present invention will be further described below with reference to the accompanying drawings and embodiments:

[0068] Figure 1 This is a schematic diagram of the process of the present invention.

[0069] Figure 2 Diagram of water level detection data processing model. Detailed Implementation

[0070] The invention will now be described in further detail with reference to the accompanying drawings and tables.

[0071] The flowchart illustrates the method for transmitting redundant measurement values ​​from a single-point water level gauge in a ship lock chamber. Figure 1 As shown, the specific operation steps are as follows:

[0072] Step 1: Data acquisition and storage. The water level at a certain detection point in the lock chamber is detected simultaneously by N water level gauges. At a certain moment, multiple water level detection values ​​of the detection point are obtained as Vn, n=1,2,...,N; the water level detection values ​​of 3 water level gauges are shown in Table 1.

[0073] Table 1. Water level readings from three water level gauges

[0074]

[0075]

[0076] Step 2: Data preprocessing. Determine the deviation range of the water level at the detection point and the deviation threshold between the water level detection values ​​from multiple water level gauges. Compare the deviation ranges of multiple water level detection values ​​Vn. Water level detection values ​​exceeding the deviation range are discarded and will not participate in the next step of data processing. Perform pairwise difference calculations on multiple water level detection values ​​Vn. If the deviation of a certain water level detection value from both of the other two water level detection values ​​exceeds the deviation threshold determined in Step 2, then that water level detection value is discarded and will not participate in the next step of data processing.

[0077] Step 3: Conduct error analysis. Parameters such as temperature, humidity, and air pressure in the water level gauge's detection environment affect its measurement accuracy. The installation location, height, and angle of the water level gauge also affect its measurement accuracy and sensitivity. Therefore, a blank test error method is used. Before installation, appropriate initial parameters are set for the water level gauge test, serving as a comparison and effectively controlling system errors.

[0078] The parameters are set as follows: temperature 23℃, humidity 50%, pressure one atmosphere, water level gauge fixed measuring point, perpendicular to the horizontal plane of the gate chamber.

[0079] Step 4: When analyzing water level monitoring data, it is also necessary to consider the impact of fluctuation factors and use machine learning methods to establish a fluctuation model in order to predict the trend and pattern of water level changes.

[0080] First, identify the multiple possible factors (a) affecting the water level. iFor each i = 1...N, to reduce model complexity, linear regression is considered instead of nonlinear regression, meaning the impact of rainfall on water levels in each basin is linear. A backward stepwise regression is performed, removing factors with the smallest absolute parameter values. The stepwise regression ends when the RMSE (root mean square error) increases while the F-value decreases. The regression results show that the main factors influencing water level fluctuations are the water level at the previous time step and the average rainfall at the previous time step.

[0081] The formula for the stepwise regression model is as follows:

[0082]

[0083] Among them: Hk i Let Rgjy be the water level in the lock chamber at time i. i-j Let be the rainfall at time j.

[0084] Step 5: Data fusion processing. Using multi-sensor data fusion technology, firstly, Kalman filtering is performed on the water level detection data from the sensors, and the noise covariance matrix is ​​measured.

[0085]

[0086] Then, a fuzzy evaluation of the sub-filter's reliability is performed, selecting the ratio η between the actual and theoretical values ​​of the filter innovation divergence. i (k) and the trace tr(p) of the state estimation error covariance. i (k) is used as a fuzzy evaluation parameter for the credibility of sub-filters to establish a fuzzy evaluation of filter credibility.

[0087] Select the parameters and perform the following transformation:

[0088] p Fi (k)=|tr(p i (k))|

[0089] CE I (k)=|η i (k)-1|

[0090] These are used as input values ​​for the fuzzy observer. The fuzzy subset of the input is defined as: {Z(zero), SE(smaller), S(smaller), B(larger), BE(larger)}, and the universe of discourse is chosen to be [0, 1].

[0091] The output ζ of the fuzzy observer i (k) represents the confidence level of each filter, and its universe of discourse is [0, 1]. Its fuzzy subset is defined as: {VL (lower), L (lower), M (medium), H (higher), VH (higher)}, and its fuzzy membership function is shown in Table 2.

[0092] Table 2 Fuzzy Membership Function Table

[0093]

[0094] Calculate the weighting factors:

[0095]

[0096] N represents the number of sensors in the fusion system.

[0097] The weighting coefficients and the estimated state values ​​X of each sub-filter i (k) derives the global estimate X(k) and outputs the comprehensive calculation result.

[0098]

[0099] Step 6: The effective value refers to the effective value obtained after averaging the signal during its change process. It has the same power as the original signal and can more accurately reflect the signal strength.

[0100] The values ​​obtained after secondary processing are further processed to obtain the effective water level detection values, using the following formula:

[0101]

[0102] Among them, V RMS V represents the valid value of the water level detection, V(i) represents the i-th data point sampled, and N represents the number of data points sampled.

[0103] Step 7: The effective value of the water level detection is processed into a standard electrical signal and then output, including A / D conversion, D / A conversion, and signal amplification, outputting a 4-20mA electrical signal.

Claims

1. A method for transmitting redundant measurement values ​​of a single-point water level gauge in a lock chamber, characterized in that... Includes the following steps: Step 1: Simultaneously detect the water level at a certain detection point in the lock chamber using N water level gauges, and obtain multiple water level detection values ​​at that detection point at a certain moment, Vn, n=1,2,...,N; Step 2: Based on the lock chamber water level change threshold G1 and the water level gauge detection range R, determine the water level deviation threshold G2 and the detection value deviation threshold G3 of the multiple water level gauges at the detection point. Step 3: Compare the multiple water level gauge readings Vn at a certain detection point in Step 1 with the water level deviation threshold G2 determined in Step 2 for that detection point. Water level readings exceeding the water level deviation threshold G2 are discarded and do not participate in the next data processing step; the remaining M water level readings are reasonable values ​​Vm, m = 1, 2, ..., M, and participate in the next data processing step. Step 4: Perform a difference calculation on the reasonable water level detection value Vm obtained in Step 3. If the deviation between a certain water level detection value and the other two water level detection values ​​exceeds the deviation threshold determined in Step 2, then the water level detection value is eliminated and will not participate in the next data processing step; at the same time, the water level gauge corresponding to the water level detection value is cut off. Step 5: The N1 water level detection values ​​Vi, i = 1, 2, ..., N1 after step 4 are used as the basic data for water level detection at this detection point. They are then processed to obtain the effective water level detection value at this detection point. Step Six: Process and output the valid water level detection values ​​from Step Five; The secondary processing in step five includes the following steps: S5.1 Error Analysis: The analysis is based on a water level detection data processing model established by considering the water level gauge detection environment, water level gauge installation method, and factors affecting water level fluctuations in the gate chamber. S5.2 Data Fusion Processing: Using multi-sensor data fusion technology, the Kalman filter is first applied to the water level detection data from the sensors, and the noise covariance matrix is ​​measured. Then, a fuzzy evaluation of the reliability of the sub-filters is performed, and the ratio η of the actual value to the theoretical value of the filter information divergence is selected. i (k) and the trace tr(p) of the state estimation error covariance. i (k) is used as a fuzzy evaluation parameter for the credibility of sub-filters to establish a fuzzy evaluation of filter credibility; Select the parameters and perform the following transformation: p Fi (k)=|tr(p i (k))|,CE I (k)=|η i (k)-1|, respectively, are used as the input values ​​of the fuzzy observer; the fuzzy subset of the input is defined as: {Z(zero), SE(small), S(small), B(large), BE(large)}, and the universe of discourse is selected as [0,1]; The output ζi(k) of the fuzzy observer represents the confidence level of each filter. Its universe of discourse is [0,1], and its fuzzy subset is defined as: {VL(lower), L(lower), M(medium), H(higher), VH(higher)}. Calculate the weighting factors: N is the number of sensors in the fusion system; The global estimate X(k) is derived from the weighting coefficients and the state estimates Xi(k) of each sub-filter, and the comprehensive calculation results are output.

2. The method for transmitting redundant measurement values ​​of a single-point water level gauge in a lock chamber according to claim 1, characterized in that: In step two: the water level change threshold G1 of a certain gate chamber refers to the maximum difference between the lowest water level and the highest water level of that gate chamber; The water level gauge's detection range R refers to the maximum water level change that the water level sensor can measure. The water level deviation threshold G2 includes the dynamic water level deviation threshold and the static water level deviation threshold. The dynamic water level deviation threshold refers to the maximum limit of water level change per minute under the state of filling and draining water. The static water level deviation threshold refers to the absolute value of the water level change at the detection point per minute under conditions of no water filling or draining. The detection value deviation threshold G3 refers to the maximum deviation limit between the detection values ​​of multiple sensors at the same detection point at the same time. This value reflects the degree of concentration between the detection values ​​of redundant sensors at a single measurement point and can be used to judge the reliability of water level detection at a single measurement point.

3. The method for transmitting redundant measurement values ​​of a single-point water level gauge in a lock chamber according to claim 1, characterized in that: In step four: the reasonable water level detection value refers to the water level detection value Vm, m=1,2,...,M, M≤N, which is within the deviation range.

4. The method for transmitting redundant measurement values ​​of a single-point water level gauge in a lock chamber according to claim 1, characterized in that: S5.1 includes: ①: Under the water level gauge testing environment, the blank test error method is used. Before the water level gauge is installed, appropriate initial environmental parameters are set for water level gauge testing. If the actual environmental reading is higher or lower than the initial environmental reading, an appropriate calibration coefficient is selected to calibrate the water level gauge measurement value to the parameters of the current environment. ②: When analyzing water level monitoring data, the influence of the installation method should be considered, and the data should be corrected and adjusted according to the following steps: (1) Check the installation position and orientation of the water level gauge, such as the installation height and angle; avoid errors caused by vibration or movement, and ensure that the water level gauge is placed in a horizontal position; (2) Correcting zero point error: Zero point error refers to the situation where the reading is not zero when the water level gauge is in a horizontal position within the measurement range of the water level gauge; when the water level gauge is kept in a horizontal position, adjust the zero point offset to make the reading zero. (3) Perform proportional error correction: proportional error refers to the difference between the reading and the actual water level when the water level gauge is in a horizontal position within the measurement range of the water level gauge; proportional error is corrected by calibrating the water level gauge at a known water level; if the reading is too high or too low, the proportional error is corrected by adjusting the coefficient of the water level gauge. ③: Considering the influence of water flow inertia during lock filling and emptying, the water level fluctuation change in the lock chamber is solved by a two-dimensional unsteady flow mathematical model of lock chamber water surface fluctuation and a one-dimensional mathematical model of lock filling and emptying. The fundamental equations for planar two-dimensional unsteady water flow motion, including second-order turbulence terms, are as follows: Continuity equation equations of motion Where H = ζ + d is the total water depth, d is the water depth, ζ is the water level; u is the x-direction flow velocity, v is the y-direction flow velocity, and ρ is the density of water. The stress is at the bottom in the x-direction; The stress is at the bottom in the y-direction; is the Chezy coefficient; n is the Manning roughness coefficient. It is the turbulent viscosity coefficient; The basic hydraulic equations considering inertial effects and the lock filling and emptying process are as follows: Equation for water level change within the sluice gate chamber: Where: Z is the water level in the gate chamber, V is the average flow velocity of the calculated cross-section of the corridor, μ is the flow coefficient, and L... m ω is the converted length of the water conveyance corridor, ω is the calculated cross-sectional area of ​​the water conveyance corridor, and Ω is the water surface area of ​​the gate chamber.

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