A method for measuring sediment transport rate in open-channel cross-section based on multi-sensor array

Abstract

The present invention discloses a method for measuring sediment transport volume of open channel cross-section based on multi-sensor array, comprising the following steps: 1) Sampling sediment transport volume measurement parameter q; 2) Standardizing to obtain standardized data Q; 3) Calculating to obtain the standardized covariance matrix R of Q Q , as well as eigenvalue λ and eigenvector t; 4) Selecting main influencing factors to determine the first main influencing factor, the second main influencing factor,..., the z-th main influencing factor; 5) Calculating to obtain the determination coefficient R 2 , root mean square error RMSE, and mean absolute error MAE; If R 2 < R d , RMSE < RMSE d and MAE < MAE d , then this set of sediment transport volume measurement parameters is valid, otherwise return to step 1) to resample the sediment transport volume measurement parameters: 6) Calculating the sediment transport volume C according to the valid sediment transport volume measurement parameters s . The sediment transport volume measurement method of the present invention greatly improves the measurement accuracy of the sediment transport volume of open channels and ensures the effective monitoring of the sediment condition of water bodies.

Description

Technical Field

[0001] The present invention relates to the technical field of sediment transport measurement, and particularly to a method for measuring the sediment transport of an open channel cross-section based on a multi-sensor array. Background Art

[0002] The phenomenon of global soil erosion is becoming increasingly serious. To control sediment, the primary problem is to be able to effectively monitor the sediment condition of water bodies and obtain real-time and accurate suspended sediment concentration data, which is very important for studying the sediment transport process. In China, the research on the sediment transport process has a long history, but most of it belongs to theoretical research, and many accurate measurement results come from small and medium-scale measurements. There is less experience in the real-time monitoring of the sediment transport process of large rivers and harbors, and the monitoring technology lacks in-depth research.

[0003] Currently, the commonly used method for measuring sediment transport is to calculate the sediment transport of the cross-section after obtaining the flow rate and sediment concentration. The flow rate measurement can be calculated through methods such as the velocity-area method, and there are mainly three methods for measuring sediment concentration, namely traditional manual sampling and analysis methods (such as drying method, specific gravity method, etc.), acoustic measurement methods (ADCP, etc.) and optical measurement methods (optical scattering, optical projection, etc.). However, the influence of the particle size and chromaticity of the sediment in water on the measurement process is not considered during the measurement of sediment concentration. The accuracy of sediment transport measurement needs to be improved. Summary of the Invention

[0004] In view of the above-mentioned defects or deficiencies in the prior art, it is desirable to provide a method for measuring the sediment transport of an open channel cross-section based on a multi-sensor array, which respectively measures factors such as water depth, flow velocity, temperature, sediment concentration, sand particle size, and sand particle surface chromaticity, and calculates the sediment transport of the cross-section by analyzing the influence effects and weights of different factors. This method greatly improves the measurement accuracy of the sediment transport in the open channel and ensures the effective monitoring of the sediment condition of water bodies.

[0005] A method for measuring the sediment transport of an open channel cross-section based on a multi-sensor array provided by the present invention includes the following steps:

[0006] 1) Sampling the sediment transport measurement parameters q at time intervals T respectively, where the sediment transport measurement parameters include water depth value q1, flow velocity value q2, temperature value q3, sediment concentration value q4, sand particle size value q5, and sand particle surface chromaticity value q6;

[0007]

[0008] 2) Standardizing the sediment transport measurement parameters to obtain standardized data Q;

[0009] The standardized data Q is:

[0010]

[0011] Wherein:

[0012]

[0013] 3) Calculate the standardized covariance matrix R of Q Q , and the eigenvalues λ of R Q and the eigenvectors t corresponding to the eigenvalues λ;

[0014] The standardized covariance matrix R Q is:

[0015]

[0016] The calculation formula for the eigenvalue λ is:

[0017] R Q Q - λQ = 0;

[0018] Wherein, the eigenvalues λ1 ≥ λ2 … ≥ λ y ≥ 0, y ≤ 6;

[0019] The eigenvector corresponding to the eigenvalue λ h is t h , h = 1, 2,..., y;

[0020]

[0021] 4) Select the main influencing factors, and calculate the contribution rate M of the main influencing factors corresponding to each sediment transport measurement parameter j and the cumulative contribution rate ∑M j ;

[0022] Wherein, the sediment transport measurement parameters with the cumulative contribution rate ∑M j ≥ 0.85 are the main influencing factors, and then determine the first main influencing factor, the second main influencing factor,..., the z-th main influencing factor according to the M j values from large to small, z ≤ the number of types of sediment transport measurement parameters;

[0023] The contribution rate M of the main influencing factor j is:

[0024]

[0025] The cumulative contribution rate ∑M j is:

[0026]

[0027] 5) Establish a calculation model, and obtain the calculated value of sediment concentration through the calculation of the calculation model; conduct on-site actual measurement of sediment concentration to obtain the true value of sediment concentration; calculate and obtain the determination coefficient R from the calculated value of sediment concentration and the true value of sediment concentration 2 , root mean square error RMSE, and mean absolute error MAE; if R 2 < R d , RMSE < RMSE d and MAE < MAE d , then this set of sediment transport measurement parameters is valid; otherwise, return to step 1) to resample the sediment transport measurement parameters;

[0028] Among them, R d is the preset determination coefficient threshold, RMSE d is the preset root mean square error threshold, and MAE d is the preset mean absolute error threshold:

[0029] The calculation model is:

[0030] Construct rule i: If x1 = A i , x2 = B i , x3 = C i , x4 = D i , x5 = E i , x6 = F i , then:

[0031] f i = t i1 x1 + t i2 x2 +... + t iz x z ;

[0032] Among them, i = 1, 2,..., z; A i , B i , C i , D i , E i , F i are the non-linear parameters corresponding to rule i;

[0033] The first layer of the calculation model: Fuzzify the input signal of the main influencing factors, and the membership degree value of the i-th node is:

[0034]

[0035] Among them, {m i , n i , k i} is the adaptability variable;

[0036] The second layer of the calculation model: Calculate the triggering intensity w i ;

[0037]

[0038] The third layer of the calculation model: Obtain the normalized trigger intensity according to the second layer

[0039]

[0040] The fourth layer of the calculation model: Calculate the rule output, and calculate the contribution of the i-th rule to the model output:

[0041]

[0042] The fifth layer of the calculation model: Defuzzification to obtain the calculated value of sediment concentration:

[0043]

[0044] 6) Calculate the sediment transport rate C according to the effective sediment transport rate measurement parameters s ;

[0045]

[0046] Furthermore, the coefficient of determination R 2 is:

[0047]

[0048] The root mean square error RMSE is:

[0049]

[0050] The mean absolute error MAE is:

[0051]

[0052] Wherein, is the true value of the sediment concentration in the i-th on-site actual measurement; is the true average value of the sediment concentration in the previous i on-site actual measurements; m is the total number of on-site actual measurements of the sediment concentration.

[0053] Compared with the prior art, the beneficial effects of the present invention are:

[0054] The sediment transport rate measurement method of the present invention respectively samples the sediment transport rate measurement parameters q related to the calculation of the sediment transport rate through multiple sensors, determines the main influencing factors therefrom through calculation, that is, the sediment transport rate measurement parameters that have a greater impact on the calculation of the sediment transport rate. Then, the coefficient of determination R is obtained through calculation 2, the root mean square error RMSE and the mean absolute error MAE; then, by comparison, it is determined whether the obtained sediment transport measurement parameter q is valid. If it is invalid, the sediment transport measurement parameter q is obtained again; if it is valid, the sediment transport C is calculated according to the valid sediment transport measurement parameter s . The sediment transport measurement method of the present invention greatly improves the measurement accuracy of open channel sediment transport and ensures the effective monitoring of the sediment condition of water bodies. It provides a data basis for the analysis of hydraulic characteristics, water resource allocation, and the balance of river ecosystems, and provides technical support for decision-making and measures in aspects such as water resource management, environmental protection, river engineering planning, and flood control projects

[0055] It should be understood that the content described in the summary of the invention is not intended to limit the key or important features of the embodiments of the present invention, nor to limit the scope of the present invention. Other features of the present invention will become easily understood through the following description BRIEF DESCRIPTION OF THE DRAWINGS

[0056] By reading the detailed description of the non-limiting embodiments with reference to the following drawings, other features, objects, and advantages of the present invention will become more apparent

[0057] Figure 1 It is a flowchart of a method for measuring open channel cross-section sediment transport based on a multi-sensor array DETAILED DESCRIPTION OF THE INVENTION

[0058] The present invention will be further described in detail below with reference to the drawings and embodiments. It can be understood that the specific embodiments described herein are only used to explain the related invention and do not limit the invention. Additionally, it should be noted that for the sake of description, only parts related to the invention are shown in the drawings

[0059] It should be noted that, without conflict, the embodiments in the present invention and the features in the embodiments can be combined with each other. The present invention will be described in detail below with reference to the drawings and embodiments

[0060] Please refer to Figure 1 , the embodiments of the present invention provide a method for measuring open channel cross-section sediment transport based on a multi-sensor array, including the following steps

[0061] 1) Sample the sediment transport measurement parameter q at time intervals T respectively, including the water depth value q1, the flow velocity value q2, the temperature value q3, the sediment concentration value q4, the sand particle size value q5, and the sand particle surface chromaticity value q6

[0062]

[0063] 2) Standardize the sediment transport measurement parameter to obtain the standardized data Q. The standardized data Q is

[0064]

[0065] Among them:

[0066]

[0067] 3) Calculate the standardized covariance matrix R of Q Q , and the eigenvalues λ of R Q and the eigenvectors t corresponding to the eigenvalues λ;

[0068] The standardized covariance matrix R Q is:

[0069]

[0070] The calculation formula for the eigenvalue λ is:

[0071] R Q Q - λQ = 0;

[0072] Among them, the eigenvalues λ1 ≥ λ2 … ≥ λ y ≥ 0, y ≤ 6;

[0073] The eigenvector corresponding to the eigenvalue λ h is t h , h = 1, 2, ..., y;

[0074]

[0075] 4) Select the main influencing factors, and calculate the contribution rate M of the main influencing factors corresponding to each sediment transport measurement parameter j and the cumulative contribution rate ∑M j ;

[0076] The contribution rate M of the main influencing factor j is:

[0077]

[0078] The cumulative contribution rate ∑M j is:

[0079]

[0080] Among them, the sediment transport measurement parameters with the cumulative contribution rate ∑M j ≥ 0.85 are the main influencing factors, and then according to the M j values, the first main influencing factor, the second main influencing factor, ..., the z-th main influencing factor are determined from large to small, z ≤ the number of types of sediment transport measurement parameters;

[0081] 5) Establish a calculation model, and calculate the sediment concentration calculation value through the calculation model;

[0082] The calculation model is as follows:

[0083] Build rule i: If x1 = A i , x2 = B i , x3 = C i , x4 = D i , x5 = E i , x6 = F i , then:

[0084] f i = t i1 x1 + t i2 x2 +... + t iz x z , i = 1, 2,..., z;

[0085] Among them, A i , B i , C i , D i , E i , F i are the non - linear parameters corresponding to rule i;

[0086] The first layer of the calculation model: Fuzzify the input signal of the main influencing factors. The membership degree value of the i - th node is:

[0087]

[0088] Among them, {m i , n i , k i} is the adaptive variable;

[0089] The second layer of the calculation model: Calculate the triggering intensity w i ;

[0090]

[0091] The third layer of the calculation model: Obtain the normalized triggering intensity according to the second layer

[0092]

[0093] The fourth layer of the calculation model: Calculate the rule output, and calculate the contribution of the i - th rule to the model output:

[0094]

[0095] The fifth layer of the calculation model: Defuzzify to obtain the sediment concentration calculation value:

[0096]

[0097] The actual sediment concentration is measured on-site to obtain the true value of the sediment concentration; the coefficient of determination R is calculated from the calculated value of the sediment concentration and the true value of the sediment concentration. 2 The root mean square error RMSE and the mean absolute error MAE are obtained.

[0098] The coefficient of determination R 2 is:

[0099]

[0100] The root mean square error RMSE is:

[0101]

[0102] The mean absolute error MAE is:

[0103]

[0104] where is the true value of the sediment concentration measured on-site for the i-th time; is the average true value of the sediment concentration measured on-site for the first i times; m is the total number of on-site actual measurements of the sediment concentration.

[0105] If R 2 < R d and RMSE < RMSE d and MAE < MAE d , then this set of sediment transport rate measurement parameters is valid; otherwise, return to step 1) to resample the sediment transport rate measurement parameters.

[0106] where R d is the preset coefficient of determination threshold, RMSE d is the preset root mean square error threshold, and MAE d is the preset mean absolute error threshold:

[0107] 6) Calculate the sediment transport rate C according to the valid sediment transport rate measurement parameters s :

[0108]

[0109] In this embodiment, when measuring the sediment transport rate, the sediment transport rate measurement parameters q related to the calculation of the sediment transport rate are continuously sampled by multiple sensors, and the standardized data Q is obtained after standardized processing, and then the covariance matrix R Q , the eigenvalue λ and the eigenvector t are obtained through calculation; then the contribution rate M j of the main influencing factors corresponding to each sediment transport rate measurement parameter and the cumulative contribution rate ∑M j are calculated, and the main influencing factors, that is, the sediment transport rate measurement parameters with a greater impact on the calculation of the sediment transport rate, are determined.

[0110] Then, a calculation model is established to calculate the calculated sediment concentration value, and the actual measurement of the sediment concentration is carried out on-site to obtain the true sediment concentration value; the coefficient of determination R is calculated from the calculated sediment concentration value and the true sediment concentration value. 2 , the root mean square error RMSE and the mean absolute error MAE are calculated. Then, by comparison, it is determined whether the obtained sediment transport measurement parameter q is valid. If it is invalid, the sediment transport measurement parameter q is obtained again; if it is valid, the sediment transport C is calculated according to the valid sediment transport measurement parameter. s .

[0111] The sediment transport measurement method of the present invention greatly improves the measurement accuracy of the sediment transport in open channels, ensures the effective monitoring of the sediment status of water bodies, provides a data basis for the analysis of hydraulic characteristics, water resource allocation, and the balance of river ecosystems, and provides technical support for decision-making and measures in aspects such as water resource management, environmental protection, river engineering planning, and flood control projects.

[0112] In the description of this specification, the descriptions of terms such as "one embodiment", "some embodiments", etc. mean that the specific features, structures, materials, or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of the present application. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or instance. Moreover, the specific features, structures, materials, or characteristics described can be combined in a suitable manner in any one or more embodiments or examples.

[0113] The above are only the preferred embodiments of the present application and are not used to limit the present application. For those skilled in the art, various changes and modifications can be made to the present application. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application shall be included in the protection scope of the present application.

Claims

1. A method for measuring sediment transport in an open channel section based on a multi-sensor array, characterized in that: The steps include: 1) Sampling sediment transport measurement parameters q at time intervals T, wherein the sediment transport measurement parameters include water depth value q1, flow velocity value q2, temperature value q3, sediment content value q4, sand particle size value q5, and sand particle surface chromaticity value q6; 2) Standardizing the sediment transport measurement parameters to obtain standardized data Q; The standardized data Q is: 3) Calculate the standardized covariance matrix R of Q Q , and R Q The eigenvalue λ of and the eigenvector t corresponding to the eigenvalue λ; The standardized covariance matrix R Q for: The calculation formula of the eigenvalue λ is: R Q Q-λQ=0; Among them, the eigenvalues ​​λ1≥λ2…≥λ y ≥0, y≤6; The eigenvalue λ h The corresponding eigenvector is t h , h=1,2,...,y; 4) Select the main influencing factors and calculate the contribution rate M of the main influencing factors corresponding to each sediment transport measurement parameter j And the cumulative contribution rate ∑M j ; Among them, the cumulative contribution rate ∑M j The sediment transport measurement parameters with a value of ≥0.85 are the main influencing factors. j The values ​​are determined from large to small to determine the first main influencing factor, the second main influencing factor, ..., the zth main influencing factor, where z ≤ the number of types of sediment transport measurement parameters; The contribution rate of the main influencing factors M j for: The cumulative contribution rate ∑M j for: 5) Establish a calculation model, and obtain the calculated value of the sand content through the calculation model; conduct actual measurement of the sand content on site to obtain the true value of the sand content; calculate the determination coefficient R from the calculated value of the sand content and the true value of the sand content 2 , root mean square error RMSE, mean absolute error MAE; if R 2 <R d 、RMSE <RMSE d And MAE <MAE d , then the set of sediment transport measurement parameters is valid, otherwise return to step 1) to resample the sediment transport measurement parameters; Among them, R d is the preset determination coefficient threshold, RMSE d is the preset root mean square error threshold, MAE d is the preset mean absolute error threshold: The calculation model is: Construct rule i: If x1 = A i , x2=B i , x3=C i , x4=D i , x5=E i , x6=F i ,but: f i =t i1 x1+t i2 x2+...+t iz x z ,i=1,2,…,z; Among them, A i , B i , C i , D i 、E i 、F i is the nonlinear parameter corresponding to rule i; The first layer of the calculation model: the input signal of the main influencing factor is fuzzy processed, and the membership value of the i-th node is: Among them, {m i ,n i ,k i } is the adaptive variable; Computational model layer 2: Calculate the trigger strength w of each fuzzy rule i ; Computational model layer 3: Normalized trigger strength obtained based on the second layer Calculation model layer 4: Calculate rule output and calculate the contribution of the i-th rule to the model output: Calculation model layer 5: Defuzzification, obtaining the calculated value of sand content: 6) Calculate the sediment transport C based on the effective sediment transport measurement parameters s ; 2. The method for measuring sediment transport in an open channel section based on a multi-sensor array according to claim 1, characterized in that: The coefficient of determination R 2 for: The root mean square error RMSE is: The mean absolute error MAE is: in, is the true value of the sediment content measured on site for the i-th time; is the true average value of the actual on-site measurements of the previous i times; m is the total number of actual on-site measurements of the sand content.

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