Method and system for judging health degree of flood discharge deep hole control system based on entropy weight method

Abstract

The invention relates to a flood discharge deep hole control system health degree judgment method based on an entropy weight method. Influence factors of the health degree of a flood discharge deep hole control system are determined; constructing an influence factor index data matrix, and carrying out dimensionless processing on influence factor index data; calculating the weight of the influence of each influence factor index on the health degree of the flood discharge deep hole control system by adopting an entropy weight method; determining positive and negative ideal solutions of various influence factor indexes; calculating the health degree of the flood discharge deep hole control system according to the distances from the positive ideal solution to the negative ideal solution, constructing an optimal hyper-sphere model of the flood discharge deep hole control system, and calculating the health degree, namely a health degree threshold value, of a data sample in an optimal hyper-sphere upper critical state. Whether the flood discharge deep hole facility control system in the real-time working condition is in the healthy state or not is judged according to the health degree of the flood discharge deep hole facility control system, the flood discharge deep hole facility control system in the unhealthy state is overhauled and maintained, and it is ensured that the flood discharge deep hole facility operates healthily, safely and stably.

Description

Technical Field

[0001] The invention belongs to the field of dam safety monitoring, and in particular relates to a method and system for determining the health of a flood discharge deep hole control system based on an entropy weight method. Background Art

[0002] The deep holes of the dam are mainly responsible for the flood discharge of the dam. The health of the deep hole control system directly reflects its operating status. A high health indicates a good condition, while a low health indicates the risk of refusal to operate or misoperation, and the flood control performance is reduced. In severe cases, there is a risk of dam overflow and collapse. Therefore, it is very important to calculate and pay attention to the health of the deep hole control system for the maintenance of flood control facilities.

[0003] The existing health assessment method for flood discharge deep hole control systems is mainly the threshold judgment method, which compares the factor index value with its threshold value. Factors above the threshold are marked as qualified, and factors below the threshold are marked as unqualified.

[0004] The existing health assessment methods for flood discharge deep hole control systems have the following shortcomings: (1) The independent variable is single, and only a single factor indicator is used to judge whether it is qualified or unqualified. There is no systematic analysis of the factors affecting the health of the flood discharge deep hole control system, and there is a lack of combining multiple influencing factor indicators for overall judgment.

[0005] (2) The judgment result is single. The health judgment results of the flood discharge deep hole control system are only qualified or unqualified, and it is impossible to know the health status of the flood discharge deep hole control system. Summary of the invention

[0006] The purpose of the present invention is to address the above problems and provide a method for determining the health of a deep hole control system for flood discharge based on the entropy weight method, construct a multi-dimensional influencing factor index, and use the entropy weight method to determine the weight of each influencing factor index on the health of the deep hole control system for flood discharge. The health of the deep hole facility control system is calculated based on the distance from the positive and negative ideal solutions of the influencing factor index of the deep hole facility control system for flood discharge, and whether the deep hole facility control system for flood discharge in real-time working conditions is in a healthy state is judged based on the health of the deep hole facility control system.

[0007] In order to achieve the above object, the technical solution provided by the present invention is: The method for determining the health of a flood discharge deep hole control system based on the entropy weight method includes the following steps: Step 1: Determine the factors affecting the health of the flood discharge deep hole control system; Step 2: Obtain the influencing factor indicator data; Step 2.1: Construct the data matrix of influencing factors and indicators; Step 2.2: Dimensionless processing of the influencing factor indicator data; Step 3: Use the entropy weight method to calculate the weight of each influencing factor index on the health of the flood discharge deep hole control system; Step 4: Determine the positive and negative ideal solutions for various influencing factor indicators; Step 5: Calculate the health of the flood discharge deep hole control system according to the distance from the positive and negative ideal solutions; Step 6: Construct an optimal hypersphere model of the influencing factors of the deep hole flood discharge control system. Use the method in step 5 to calculate the health of the sample data in the critical state on the optimal hypersphere as the health threshold. Compare the health of the deep hole flood discharge control system under real-time conditions with the health threshold to determine whether the deep hole flood discharge control system needs to be inspected and maintained due to safety risks.

[0008] Preferably, the influencing factor indicators of the health of the flood discharge deep hole control system include the oil level of the high-level oil tank, the arc gate opening, the incoming line voltage, the oil cylinder temperature and the oil cylinder oil level.

[0009] Furthermore, in step 2, at every time T, the index data of various influencing factors of each flood discharge deep hole are obtained to calculate the current health degree, and the original influencing factor index data matrix R=(r ij ) mx5 , ; Where r ij , i=1,2,...m; j=1,2,...5 represents the index value of the jth influencing factor of the ith flood discharge deep hole, and m is the number of flood discharge deep holes.

[0010] Preferably, in step 3, the specific process of using the entropy weight method to calculate the weight of each influencing factor index includes: According to the definition of entropy, the weight matrix of influencing factor indicators is calculated. P=(p ij ) mx5 ; ; In the formula The element in the i-th row and j-th column of the standardized data matrix representing the influencing factor index, p ij express The proportion of According to the weight matrix P, the entropy value of each influencing factor index is calculated. ; In the formula represents the entropy value of the j-th influencing factor index, j=1,2,...,5; Calculate the entropy weight of the jth influencing factor index , ; The column vector of the entropy weight matrix of the influencing factor index is ; The entropy weight matrix is ​​used to weight the standardized data matrix to obtain the weighted standardized matrix Z of the influencing factor indicators. ; In the formula Represents the element in the i-th row and j-th column of the weighted standardized matrix of the influencing factor index.

[0011] Preferably, in step 5, the calculation process of the health of the flood discharge deep hole control system includes: Calculate the Euclidean distance D between the sample data of the influencing factor index and the positive and negative ideal solutions + and D - , ; ; In the formula The element in the i-th row and j-th column of the weighted standardized matrix of the influencing factor index is represented by represents the maximum value of the j-th influencing factor index, It represents the minimum value of the j-th influencing factor index; The health of the i-th deep hole control system is calculated based on the Euclidean distance between the positive and negative ideal solutions. ; In the formula Represents the health of the i-th deep hole control system.

[0012] Preferably, in step 6, constructing an optimal hypersphere model of influencing factor indicators of the flood discharge deep hole facility control system specifically includes: (1) Constructing a sample data set of indicators of factors influencing the health of a deep hole control system for flood discharge, wherein the sample data set contains data samples of indicators of factors influencing the health of a deep hole control system for flood discharge in a healthy state and an unhealthy state; (2) performing data cleaning and dimensionless processing on the sample data set; (3) constructing a minimum hypersphere containing healthy state sample data, where the minimum hypersphere is as far away from unhealthy state sample data as possible; (4) Train and adjust the model parameters of the minimum hypersphere to obtain the optimal hypersphere.

[0013] As another invention object of the present invention, a health determination system for a dam flood discharge deep hole control system comprises: The data acquisition module is used to obtain sample data of factors affecting the health of the deep hole control system.

[0014] The preprocessing module is used to preprocess the sample data acquired by the data acquisition module to obtain a standardized data matrix of the sample data.

[0015] The entropy weight calculation module calculates the weight of each influencing factor index on the health of the flood discharge deep hole control system based on the entropy weight method, determines the entropy weight matrix column vector of the influencing factor index of the flood discharge deep hole control system, and calculates the weighted standardized matrix of the data sample.

[0016] The health degree calculation module calculates the health degree of the current flood discharge deep hole control system corresponding to the sample data according to the distance between the sample data of the influencing factor index of the flood discharge deep hole control system and the positive and negative ideal solutions.

[0017] The optimal hypersphere module constructs a minimum hypersphere containing healthy state sample data based on the indicator data samples of the health influencing factors of the flood discharge deep hole control system in healthy and unhealthy states, trains and adjusts the model parameters of the minimum hypersphere to obtain the optimal hypersphere.

[0018] The health threshold calculation module calls the health calculation module to calculate the health of the critical state sample data on the optimal hypersphere, that is, the health threshold.

[0019] The alarm module uses the real-time health of the flood discharge deep hole control system calculated by the health calculation module and compares it with the health threshold. If the real-time health of the flood discharge deep hole control system is lower than the health threshold, a safety risk alarm signal of the flood discharge deep hole control system is issued.

[0020] Preferably, the optimal hypersphere model is retrained regularly with new sample data of influencing factors of the deep hole facility control system of the flood discharge, so that the optimal hypersphere model can reflect the operational changes of the dam flood discharge deep hole control system over time. Compared with the prior art, the beneficial effects of the present invention include: (1) The present invention systematically determines the influencing factors of the deep hole facility control system, constructs a multi-dimensional influencing factor index, and calculates the health of the deep hole facility control system according to the distance from the positive and negative ideal solutions of the influencing factor index of the deep hole facility control system. According to the health of the deep hole facility control system, it is judged whether the deep hole facility control system of the flood discharge facility is in a healthy state in real-time working conditions, and carries out inspection and maintenance work on the deep hole facility control system in an unhealthy state, so as to ensure the healthy, safe and stable operation of the deep hole facility and effectively guarantee the safe operation of the dam.

[0021] (2) The present invention adopts the entropy weight method to determine the weight of each influencing factor index on the health of the deep hole control system for flood discharge, and realizes the quantitative calculation of the different degrees of influence of the oil level of the high-level oil tank in the deep hole opening and closing room for flood discharge, the arc gate opening, the incoming line voltage, the hydraulic system cylinder temperature, and the oil level on the health of the deep hole control system for flood discharge.

[0022] (3) The present invention trains the optimal hypersphere model with new sample data regularly, so that the optimal hypersphere model and the health threshold are timely, which can reflect the operation changes of the deep hole control system of flood discharge over time, and improve the accuracy of the health judgment result of the deep hole control system of flood discharge.

[0023] (4) The health status determination system of the deep hole control system for flood discharge provided by the present invention can calculate the health status of the control system of the deep hole facility for flood discharge of the dam in real-time working conditions, thereby realizing real-time online monitoring of the health status of the deep hole facility control system for flood discharge.

[0024] (5) When the method and system of the present invention determines that the flood discharge deep hole control system is in an unhealthy state, an alarm signal is sent to the operation and maintenance personnel, so that timely inspection and maintenance measures can be taken to improve the reliability of the dam's flood control capacity and ensure the safe operation of the dam. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] The present invention will be further described below in conjunction with the accompanying drawings and embodiments.

[0026] Figure 1 The present invention is a flowchart of a method for determining the health of a dam flood discharge deep hole control system according to an embodiment of the present invention.

[0027] Figure 2 A schematic diagram of constructing an optimal hypersphere model according to an embodiment of the present invention. DETAILED DESCRIPTION

[0028] like Figure 1 As shown in the figure, the health determination method of the flood discharge deep hole control system based on the entropy weight method includes: Step 1: Determine the factors affecting the health of the flood discharge deep hole control system; In the embodiment, the influencing factors of the health of the deep hole flood discharge control system include the oil level of the high-level tank in the deep hole flood discharge opening and closing machine room, the arc gate opening, the incoming line voltage, the hydraulic system cylinder temperature and the hydraulic system cylinder oil level.

[0029] Step 2: Obtain the influencing factor indicator data; Step 2.1: Construct the data matrix of influencing factors and indicators; In the embodiment, at every time T, the five influencing factor index data of each flood discharge deep hole are obtained through sensors to calculate the current health degree, and the original influencing factor index data matrix R=(r ij )mx5 , ; Where r ij , i=1,2,...m; j=1,2,...5 represents the index value of the jth influencing factor of the ith flood discharge deep hole, and m is the number of flood discharge deep holes.

[0030] Step 2.2: Dimensionless processing of the influencing factor indicator data; Step 2.2.1: The influencing factor index high-level fuel tank oil level is dimensionless according to formula (1). ; (1) In the formula represents the oil level value of the high-level oil tank in the hoist room of the ith flood discharge deep hole after dimensionless processing, and L is the oil replenishment rated value of the high-level oil tank in the deep hole hoist room; Step 2.2.2: The arc gate is in a closed state when it is not opened for flood discharge. The influencing factor index arc gate opening is dimensionless according to formula (2), i=1,2,...,m, ; (2) In the formula represents the arc gate opening value of the i-th flood discharge deep hole after dimensionless processing; Step 2.2.3: The influencing factor index incoming line voltage is dimensionless according to formula (3). ; (3) In the formula represents the value of the incoming line voltage of the ith flood discharge deep hole after dimensionless processing, V is the rated value of the incoming line voltage of the deep hole control system, and in the embodiment, V is 380.

[0031] Step 2.2.4: The influencing factor index cylinder temperature is dimensionless processed according to formula (4). ; (4) In the formula represents the hydraulic system cylinder temperature value of the i-th flood discharge deep hole after dimensionless processing, and C is the current room temperature of the deep hole pump room; Step 2.2.5: The influencing factor index cylinder oil level is dimensionless according to formula (5). ; (5) In the formula It represents the oil level value of the hydraulic system cylinder of the i-th flood discharge deep hole after dimensionless processing, and N is the rated value of the oil level of the cylinder in the deep hole pump room.

[0032] Step 3: Use the entropy weight method to calculate the weight of each influencing factor index on the health of the flood discharge deep hole control system; According to the definition of entropy, the weight matrix of influencing factor indicators is calculated. P=(p ij ) mx5 ; (6) ; (7) In the formula The element in the i-th row and j-th column of the standardized data matrix representing the influencing factor index, p ij express The proportion of According to the weight matrix P, the entropy value of each influencing factor index is calculated. ; (8) In the formula represents the entropy value of the j-th influencing factor index, j=1,2,...,5; Calculate the entropy weight of the jth influencing factor index , ; (9) The column vector of the entropy weight matrix of the influencing factor index is ; (10) The entropy weight matrix is ​​used to weight the standardized data matrix to obtain the weighted standardized matrix Z of the influencing factor indicators. ; (11) In the formula Represents the element in the i-th row and j-th column of the weighted standardized matrix of the influencing factor index.

[0033] Step 4: Determine the positive and negative ideal solutions for various influencing factor indicators; Step 5: Calculate the health of the flood discharge deep hole control system based on the distance from the positive and negative ideal solutions; Positive ideal solution Z + is the maximum value set of various influencing factor indicators, Z + =[ , , , , ]; Negative ideal solution Z - is the minimum value set of various influencing factor indicators, Z - =[ , , , , ]; Calculate the Euclidean distance D between the sample data of the influencing factor index and the positive and negative ideal solutions + and D - , ; (12) ; (13) In the formula The element in the i-th row and j-th column of the weighted standardized matrix of the influencing factor index is represented by represents the maximum value of the j-th influencing factor index, It represents the minimum value of the j-th influencing factor index; The health of the i-th deep hole control system is calculated based on the Euclidean distance between the positive and negative ideal solutions. ; (14) In the formula Represents the health of the i-th deep hole control system.

[0034] Step 6: Construct an optimal hypersphere model of the influencing factor indicators of the deep hole flood discharge facility control system. Use the method in step 5 to calculate the health of the sample data on the shell of the optimal hypersphere, which is in the critical state on the optimal hypersphere, as the health threshold. Compare the health of the deep hole flood discharge control system under real-time conditions with the health threshold to determine whether the deep hole flood discharge control system needs to be inspected and maintained due to safety risks.

[0035] like Figure 2 As shown in the figure, the optimal hypersphere model of the influencing factors of the flood discharge deep hole control system is constructed, including: (1) Constructing a sample data set of indicators of factors influencing the health of a deep hole control system for flood discharge, wherein the sample data set contains sample data of indicators of factors influencing the health of a deep hole control system for flood discharge in a healthy state and an unhealthy state; (2) performing data cleaning and dimensionless processing on the sample data set; (3) Construct a minimum hypersphere containing healthy sample data, which is as far away from unhealthy sample data as possible; (4) Train and adjust the model parameters of the minimum hypersphere, such as the center and radius of the hypersphere, to obtain the optimal hypersphere.

[0036] The system of the above-mentioned method for determining the health of a dam flood discharge deep hole control system comprises: The data acquisition module is used to obtain sample data of factors affecting the health of the deep hole control system.

[0037] The preprocessing module is used to preprocess the sample data acquired by the data acquisition module to obtain a standardized data matrix of the sample data.

[0038] The entropy weight calculation module calculates the weight of each influencing factor index on the health of the flood discharge deep hole control system based on the entropy weight method, determines the entropy weight matrix column vector of the influencing factor index of the flood discharge deep hole control system, and calculates the weighted standardized matrix of the sample data.

[0039] The health degree calculation module calculates the health degree of the current flood discharge deep hole control system corresponding to the sample data according to the distance between the sample data of the influencing factor index of the flood discharge deep hole control system and the positive and negative ideal solutions.

[0040] The optimal hypersphere module constructs a minimum hypersphere containing healthy state data samples based on the indicator data samples of the health influencing factors of the flood discharge deep hole control system in healthy and unhealthy states, trains and adjusts the model parameters of the minimum hypersphere to obtain the optimal hypersphere.

[0041] The health threshold calculation module calls the health calculation module to calculate the health of the critical state sample data on the optimal hypersphere, that is, the health threshold.

[0042] The alarm module uses the real-time health of the flood discharge deep hole control system calculated by the health calculation module and compares it with the health threshold. If the real-time health of the flood discharge deep hole control system is lower than the health threshold, a safety risk alarm signal of the flood discharge deep hole control system is issued.

[0043] The implementation results show that the health of the deep hole control system for flood discharge calculated by the method of the present invention can effectively identify whether the deep hole control system for flood discharge is in a healthy state and analyze the changing trend of the health of the deep hole control system for flood discharge, can meet the real-time requirements of online monitoring of the deep hole control system for flood discharge, and has self-learning function and timeliness, can adapt to the operation changes of the dam flood discharge deep hole control system over time, and ensure the accuracy of the health judgment results of the deep hole control system for flood discharge.

Claims

1. A method for determining the health of a deep hole flood discharge control system based on entropy weight method, characterized in that: The following steps are involved: Step 1: Determine the factors affecting the health of the flood discharge deep hole control system; Step 2: Obtain the influencing factor indicator data; Step 2.1: Construct the data matrix of influencing factors and indicators; Step 2.2: Dimensionless processing of the influencing factor indicator data; Step 3: Use the entropy weight method to calculate the weight of each influencing factor index on the health of the flood discharge deep hole control system; Step 4: Determine the positive and negative ideal solutions for various influencing factor indicators; Step 5: Calculate the health of the flood discharge deep hole control system based on the distance from the positive and negative ideal solutions.

2. The method for determining the health of a flood discharge deep hole control system according to claim 1 is characterized in that: The health determination method also includes step 6: constructing an optimal hypersphere model of the influencing factor indicators of the flood discharge deep hole control system, using the method of step 5 to calculate the health of the sample data in the critical state on the optimal hypersphere as the health threshold, comparing the health of the flood discharge deep hole control system under real-time working conditions with the health threshold, and judging whether the flood discharge deep hole control system needs to have safety risks and needs to carry out inspection and maintenance work.

3. The method for determining the health of a flood discharge deep hole control system according to claim 1 or 2, characterized in that: In step 1, the influencing factors of the health of the flood discharge deep hole control system include the oil level of the high-level oil tank, the arc gate opening, the incoming line voltage, the oil cylinder temperature and the oil cylinder oil level.

4. The method for determining the health of a flood discharge deep hole control system according to claim 3 is characterized in that: In step 2.1, the influencing factor index data of each flood discharge deep hole are obtained at every time T, and the original influencing factor index data matrix R = (r ij ) mx5 , ； Where r ij , i=1,2,...m; j=1,2,...5 represents the index value of the jth influencing factor of the ith flood discharge deep hole, and m is the number of flood discharge deep holes.

5. The method for determining the health of a flood discharge deep hole control system according to claim 4 is characterized in that: The step 2.2 specifically includes the following sub-steps: Step 2.2.1: The influencing factor index high-level fuel tank oil level is dimensionless according to formula (1). ；（1） In the formula represents the oil level value of the high-level oil tank in the hoist room of the ith flood discharge deep hole after dimensionless processing, and L is the oil replenishment rated value of the high-level oil tank in the deep hole hoist room; Step 2.2.2: The influencing factor index arc gate opening is dimensionless according to formula (2), i=1,2,...,m, ；（2） In the formula represents the arc gate opening value of the i-th flood discharge deep hole after dimensionless processing; Step 2.2.3: The influencing factor index incoming line voltage is dimensionless according to formula (3). ；（3） In the formula represents the value of the incoming line voltage of the ith flood discharge deep hole after dimensionless processing, and V is the rated value of the incoming line voltage of the deep hole control system; Step 2.2.4: The influencing factor index cylinder temperature is dimensionless processed according to formula (4). ；（4） In the formula represents the hydraulic system cylinder temperature value of the i-th flood discharge deep hole after dimensionless processing, and C is the current room temperature of the deep hole pump room; Step 2.2.5: The influencing factor index cylinder oil level is dimensionless according to formula (5). ； （5） In the formula It represents the oil level value of the hydraulic system cylinder of the i-th flood discharge deep hole after dimensionless processing, and N is the rated value of the oil level of the cylinder in the deep hole pump room.

6. The method for determining the health of a flood discharge deep hole control system according to claim 5 is characterized in that: In step 3, the specific process of using the entropy weight method to calculate the weight of each influencing factor index includes: According to the definition of entropy, the weight matrix P of the influencing factor index is calculated. P=(p ij ) mx5 ;(6) ；（7） In the formula The element in the i-th row and j-th column of the standardized data matrix representing the influencing factor index, p ij express The proportion of According to the weight matrix P, the entropy value of each influencing factor index is calculated. ；(8) In the formula represents the entropy value of the j-th influencing factor index, j=1,2,...,5; Calculate the entropy weight of the jth influencing factor index , ；(9) The column vector of the entropy weight matrix of the influencing factor index is ；（10） The entropy weight matrix is ​​used to weight the standardized data matrix to obtain the weighted standardized matrix Z of the influencing factor indicators. ；（11） In the formula Represents the element in the i-th row and j-th column of the weighted standardized matrix of the influencing factor index.

7. The method for determining the health of a flood discharge deep hole control system according to claim 6 is characterized in that: In step 5, the calculation process of the health of the flood discharge deep hole control system includes: Positive ideal solution Z + is the maximum value set of various influencing factor indicators, Z + =[ , , , , ]; Negative ideal solution Z - is the minimum value set of various influencing factor indicators, Z - =[ , , , , ]; Calculate the Euclidean distance D between the sample data of the influencing factor index and the positive and negative ideal solutions + and D - , ；（12） ；（13） In the formula The element in the i-th row and j-th column of the weighted standardized matrix of the influencing factor index is represented by represents the maximum value of the j-th influencing factor index, It represents the minimum value of the j-th influencing factor index; The health of the i-th deep hole control system is calculated based on the Euclidean distance between the positive and negative ideal solutions. ；（14） In the formula Represents the health of the i-th deep hole control system.

8. The method for determining the health of a flood discharge deep hole control system according to claim 2 is characterized in that: In step 6, the optimal hypersphere model of the influencing factor index of the flood discharge deep hole control system is constructed, specifically including: (1) Constructing a sample data set of indicators of factors influencing the health of a deep hole control system for flood discharge, wherein the sample data set contains sample data of indicators of factors influencing the health of a deep hole control system for flood discharge in a healthy state and an unhealthy state; (2) performing data cleaning and dimensionless processing on the sample data set; (3) constructing a minimum hypersphere containing healthy state sample data, where the minimum hypersphere is as far away from unhealthy state sample data as possible; (4) Train and adjust the model parameters of the minimum hypersphere to obtain the optimal hypersphere.

9. The system of the method for determining the health of a flood discharge deep hole control system according to claim 1, 2, 4, 5, 6, 7 or 8, characterized in that: The system comprises: The data acquisition module is used to obtain sample data of the influencing factors of the health of the deep hole control system; A preprocessing module is used to preprocess the sample data acquired by the data acquisition module to obtain a standardized data matrix of the sample data; The entropy weight calculation module calculates the weight of each influencing factor index on the health of the flood discharge deep hole control system based on the entropy weight method, determines the entropy weight matrix column vector of the influencing factor index of the flood discharge deep hole control system, and calculates the weighted standardized matrix of the sample data; The health degree calculation module calculates the health degree of the current flood discharge deep hole control system corresponding to the sample data according to the distance between the sample data of the influencing factor index of the flood discharge deep hole control system and the positive and negative ideal solutions; The optimal hypersphere module constructs the minimum hypersphere containing the healthy state sample data according to the sample data of the health influencing factors of the flood discharge deep hole control system in healthy and unhealthy states, trains and adjusts the model parameters of the minimum hypersphere to obtain the optimal hypersphere; The health threshold calculation module calls the health calculation module to calculate the health of the critical state sample data on the optimal hypersphere, that is, the health threshold.

10. The system according to claim 9, characterized in that The system also includes an alarm module, which uses the real-time health of the flood discharge deep hole control system calculated by the health calculation module and compares it with the health threshold. If the real-time health of the flood discharge deep hole control system is lower than the health threshold, a safety risk alarm signal of the flood discharge deep hole control system is issued.

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