Splitting reef cleaning intelligent control device and method

Abstract

The invention discloses a splitting reef cleaning intelligent control device and method, and relates to the technical field of splitting reef cleaning intelligent control, and the device comprises a monitoring data collection module, a monitoring data initial processing module, a monitoring index module, a model construction module and an intelligent evaluation control module. Splitting and reef cleaning monitoring data are collected through a Doppler current meter, a radar type tide level instrument, a leveling rod, a level gauge and sensor equipment, the intelligent evaluation control module evaluates the influence degree of water flow and tide on splitting equipment, corresponding measures are taken for response, and the working efficiency is improved. According to the invention, a monitoring data acquisition technology, a neural network algorithm technology and a modern information technology are closely combined, and the influence degree of water source data on the displacement of the splitting equipment and the influence degree of tide data on the water entry depth of the splitting equipment are obtained; the problem that a traditional splitting reef cleaning device and method cannot integrate multiple factors to guarantee the splitting reef cleaning precision is solved.

Description

Technical Field

[0001] The invention relates to the technical field of intelligent control for splitting and clearing reefs, and in particular to an intelligent control device and method for splitting and clearing reefs. Background Art

[0002] In the fishing port project, the reef clearing project faces many challenges, which makes the research and development of splitting reef clearing intelligent control devices and methods the key. There are a large number of reefs in the harbor and channel dredging areas, the rock strength is high and the excavation volume is large. At the same time, it is affected by complex marine environments such as large construction waves and irregular tides throughout the day, and blasting reef technology is not allowed. Traditional reef clearing methods are difficult to meet construction needs. Against this background, splitting reef clearing intelligent control devices and methods came into being. It uses a sensor system to accurately collect information such as the location, shape, and texture of the reef, uses a control system to analyze and process data and make decisions, drives the execution system to perform precise splitting operations, effectively improves the efficiency and quality of reef clearing, and ensures the smooth progress of the project. It has important reference significance for marine engineering reef clearing operations; Although the existing intelligent control devices and methods for splitting and reef clearing have made great progress, there are still some problems that need to be optimized. The existing intelligent control devices and methods for splitting and reef clearing are unable to comprehensively analyze multiple factors and control the process of splitting and reef clearing. It is difficult to ensure the accuracy of splitting and reef clearing, which affects the effect of splitting and reef clearing. Summary of the invention

[0003] The object of the present invention is to provide an intelligent control device and method for splitting and clearing reefs to solve the problems raised in the above-mentioned background technology.

[0004] In order to solve the above technical problems, the technical solutions adopted by the present invention are as follows: in the first aspect, the intelligent control device for splitting and clearing reefs includes a monitoring data acquisition module, a monitoring data initial processing module, a monitoring index module, a model building module and an intelligent evaluation control module; The monitoring data acquisition module uses Doppler current meters, radar tide gauges, leveling rods, level gauges and sensor equipment to collect monitoring data for reef clearing and splitting, providing data support for subsequent monitoring of reef clearing operations by splitting equipment; The monitoring data initial processing module pre-processes the splitting and reef clearing monitoring data and calculates the real-time displacement of the splitting equipment in all directions in three-dimensional space, thus providing a guarantee for the smooth progress of subsequent monitoring and evaluation; The monitoring indicator module is divided into a monitoring indicator unit and a monitoring evaluation unit. The monitoring indicator unit is used to obtain the displacement deviation of the splitting equipment and the degree of reef submergence; the monitoring evaluation unit is used to obtain the influence of water flow data on the displacement of the splitting equipment and the influence of tidal data on the water depth of the splitting equipment, which provides data support for building an intelligent evaluation model. The model building module builds an intelligent evaluation model through a neural network algorithm; The intelligent evaluation control module evaluates the impact of water flow and tide on the splitting equipment and takes corresponding measures to deal with it, providing a solution to the problem that traditional splitting and reef clearing devices and methods are unable to integrate multiple factors to ensure the accuracy of splitting and reef clearing.

[0005] A further improvement of the technical solution of the present invention is that the process of the monitoring data acquisition module collecting the reef-breaking monitoring data by using the Doppler current meter, the radar tide gauge, the leveling ruler, the level meter and the sensor equipment includes: The sensors include laser displacement sensors and ultrasonic sensors; The splitting reef clearing monitoring data includes water flow data, tidal data, reef data and splitting equipment working status data, wherein the water flow data is the real-time water flow velocity and its direction; the tidal data is the tide height; the reef data is the top elevation of the reef; the splitting equipment working status data is the real-time three-dimensional displacement coordinate data of the splitting equipment and the water immersion depth of the splitting equipment.

[0006] A further improvement of the technical solution of the present invention is that: the monitoring data acquisition module, the collection process of the reef-clearing monitoring data includes: A1. Calibrate the Doppler flow meter. Put the calibrated Doppler flow meter into the water and obtain the real-time water flow velocity based on the Doppler effect. The Doppler flow meter is equipped with a transducer. By measuring the difference in the sound wave frequency received by different transducers, the corresponding water flow direction is calculated. A2. Use the zero-point calibration method to place the radar tide meter in still water and adjust the zero point of the instrument. The calibrated radar tide meter transmits radar waves to the water surface. The radar waves are reflected by the water surface and received by the radar tide meter. According to the transmission and reception time of the radar waves and the propagation speed of the radar waves in the air, the distance between the radar tide meter and the water surface is calculated to obtain the tide height. A3. Fix the level rod vertically on the elevation point. Use the telescope of the level to aim the level rod. Adjust the focusing screw of the objective lens until the image of the level rod is clear. Read the reading on the level rod and record it as the rearsight reading a. Place a ruler pad on the top of the reef, fix the level rod vertically on the ruler pad, aim the level rod through the level, read the reading on the level rod and record it as the foresight reading b. According to the formula h=ab, calculate and obtain the top elevation of the reef. A4. Fix the laser displacement sensor on the splitting device, start the splitting device, output real-time displacement data through the laser displacement sensor, establish a three-dimensional coordinate system according to the structure and movement characteristics of the splitting device, transfer the real-time displacement data output by the laser displacement sensor to the three-dimensional coordinate system, and obtain the real-time three-dimensional displacement coordinate data of the splitting device; A5. Install the ultrasonic sensor on the top of the splitting device in a direction perpendicular to the water surface. Before the splitting device enters the water, measure the initial distance from the ultrasonic sensor to the water surface to obtain the total height H of the splitting device. After the splitting device enters the water, the ultrasonic sensor measures the distance n from the top of the splitting device to the water surface in real time. The real-time water depth m of the splitting device is calculated using the formula m=Hn.

[0007] A further improvement of the technical solution of the present invention is that the monitoring data initial processing module pre-processes the splitting and reef clearing monitoring data, and the process of calculating the real-time displacement of the splitting equipment in various directions in three-dimensional space includes: The splitting and reef clearing monitoring data is cleaned, and the real-time three-dimensional displacement coordinate data corresponding to two time points are extracted from the real-time three-dimensional displacement coordinate data of the splitting equipment. The two time points t1 and t2 are recorded, and the process of calculating the real-time displacement of the splitting equipment in all directions in the three-dimensional space is as follows: in, , and are the real-time displacements of the splitting device in the x-axis, y-axis and z-axis directions during the time period t1~t2 respectively; x1 and x2 correspond to the real-time displacements of the splitting device in the x-axis direction at t1 and t2 respectively; y1 and y2 correspond to the real-time displacements of the splitting device in the y-axis direction at t1 and t2 respectively; z1 and z2 correspond to the real-time displacements of the splitting device in the z-axis direction at t1 and t2 respectively.

[0008] A further improvement of the technical solution of the present invention is that the process of obtaining the displacement deviation of the splitting equipment and the degree of reef submergence by the monitoring indicator unit includes: B1. Obtain the real-time displacement components of the splitting equipment in the x, y, and z directions during the time period t1 to t2 through the real-time three-dimensional displacement data of the splitting equipment , , ; According to the direction of water flow, decompose the water flow velocity in the time period t1~t2 to obtain the water flow velocity components in the x, y, and z directions , , , set the theoretical value of water flow velocity , and ,pass = (t2-t1) formula, calculate the theoretical displacement value of the splitting device in the x-axis, y-axis and z-axis directions , , ; Using the theoretical displacement value of the splitting device , calculate the displacement deviation of the splitting device: in, , are the displacement deviations of the splitting equipment in the x-axis, y-axis and z-axis directions, , and are the real-time displacement components of the splitting device in the x-axis, y-axis and z-axis directions during the time period t1 to t2, , and are the theoretical displacement values ​​of the splitting device in the x-axis, y-axis and z-axis directions respectively; B2. The process of calculating the degree of reef inundation is as follows: in, is the degree of reef inundation, is the tide height, is the top elevation of the reef.

[0009] A further improvement of the technical solution of the present invention is that the process of obtaining the influence of water flow data on the displacement of the splitting device by the monitoring and evaluation unit includes: Combined with the theoretical displacement values ​​and displacement deviations of the splitting equipment in the x-axis, y-axis and z-axis directions, the influence of the water flow data on the displacement of the splitting equipment is calculated: in, , and are the influence of water flow data on the displacement of the splitting equipment in the x-axis, y-axis and z-axis directions, respectively. , , are the theoretical displacements of the splitting device in the x-axis, y-axis and z-axis directions, , are the displacement deviations of the splitting equipment in the x-axis, y-axis and z-axis directions respectively.

[0010] A further improvement of the technical solution of the present invention is that the process of the monitoring and evaluation unit obtaining the influence of tidal data on the water entry depth of the splitting equipment includes: The degree of reef submergence in time period i is obtained by calculation and is set as ; Extract the water depth data of the splitting equipment corresponding to the i time period from the real-time water depth data of the splitting equipment collected, and set it as ; Selecting a simple linear regression model in, Provide real-time water depth data for splitting equipment; is the degree of reef inundation, is the intercept, is the regression coefficient and represents the influence of tide data on the water depth of the splitting equipment. is the error term; Using the least squares method, calculate The process is: in, and are the average values ​​of the reef submergence degree and the water entry depth of the splitting equipment in time period i; is the reef submergence degree in time period i, is the water entry depth data of the splitting equipment in the i time period, where c=1,2,3...i; is the regression coefficient, which indicates the influence of tidal data on the water entry depth of the splitting equipment.

[0011] A further improvement of the technical solution of the present invention is that the model building module, through the neural network algorithm, builds an intelligent evaluation model, including: The neural network architecture includes an input layer, a hidden layer and an output layer. Two neurons are set in the input layer, and the two neurons receive water flow data and tidal data respectively as the input of the neural network; two hidden layers are set, and a Batch Normalization layer is added between the hidden layers to normalize the data of each layer; two neurons are set in the output layer, which respectively output the influence of water source data on the displacement of the splitting equipment and the influence of tidal data on the water entry depth of the splitting equipment; A neural network model was constructed, and the water source data and its influence on the displacement of the splitting equipment, and the tidal data and its influence on the water depth of the splitting equipment were used as data sets. The data sets were divided into a training set and a validation set in a ratio of 8:2. The training set data is input into the neural network model. Through forward propagation, the training set data is passed through the neural network layer by layer. Each layer performs weighted summation on the training set data to obtain the prediction result of the output layer. Then, through back propagation, the error between the prediction result of the output layer and the actual result is back propagated to update the weights and configuration of the network and obtain a preliminary neural network model. The performance of the preliminary neural network model was evaluated using the validation set, the model parameters were adjusted, the model was optimized, the error of the output results was reduced, and the neural network model with adjusted parameters was deployed to the reef splitting and clearing intelligent control device to obtain the intelligent evaluation model.

[0012] A further improvement of the technical solution of the present invention is that the process of the intelligent evaluation control module evaluating the influence of water flow data and tidal data on the splitting equipment and taking corresponding measures to deal with the influence includes: The water source data is input into the intelligent assessment model. When the influence of the water source data on the displacement of the splitting equipment is less than 30%, it means that the water source data has a slight impact on the splitting and reef clearing process, and the regular monitoring of the water flow data should be maintained; when the influence of the water source data on the displacement of the splitting equipment is between 30% and 50%, it means that the water source data has a moderate impact on the splitting and reef clearing process, and the splitting equipment should be equipped with additional fixed ropes and reinforced support structures; when the influence of the water source data on the displacement of the splitting equipment is greater than 50%, it means that the water source data has a severe impact on the splitting and reef clearing process, and the splitting and reef clearing operation should be stopped, the splitting equipment should be fully inspected, repaired and reinforced, and an early warning signal should be issued; The tidal data is input into the intelligent assessment model. When the influence of tidal data on the water entry depth of the splitting equipment is less than 30%, it means that the tidal data has a slight impact on the splitting and reef clearing process, and regular monitoring of tidal data should be maintained; when the influence of tidal data on the water entry depth of the splitting equipment is between 30% and 50%, it means that the tidal data has a moderate impact on the splitting and reef clearing process, and the splitting angle and force should be adjusted to control the water entry depth of the splitting equipment; when the influence of tidal data on the water entry depth of the splitting equipment is higher than 50%, it means that the tidal data has a severe impact on the splitting and reef clearing process, and the splitting and reef clearing operation should be stopped, the splitting equipment should be comprehensively inspected, and an early warning signal should be issued.

[0013] In a second aspect, a method for intelligent control of splitting and clearing reefs is provided, which is used to implement the above-mentioned intelligent control device for splitting and clearing reefs, and comprises the following steps: Step 1: Use a Doppler current meter and a radar tide meter to collect real-time water flow velocity, water flow direction and tide height, use a level ruler and a level to collect the top elevation of the reef, and use a laser displacement sensor and an ultrasonic sensor to collect real-time three-dimensional displacement coordinate data of the splitting equipment and the real-time water entry depth of the splitting equipment; Step 2: Perform data cleaning on the real-time water flow velocity, water flow direction, tide height, real-time three-dimensional displacement coordinate data of the splitting equipment and the real-time water entry depth of the splitting equipment, and calculate the real-time displacement of the splitting equipment in each direction of the three-dimensional space; Step 3: Calculate the theoretical displacement value of the splitting device in all directions of the three-dimensional space by using the water flow velocity and water flow direction, and then obtain the displacement deviation of the splitting device by combining the real-time displacement of the splitting device in all directions of the three-dimensional space; calculate the submergence degree of the reef by using the tide height and the top elevation of the reef; Step 4: Calculate the influence of water flow data on the displacement of the splitting device using the theoretical displacement and displacement deviation of the splitting device in the x-axis, y-axis and z-axis directions; obtain the influence of tidal data on the water entry depth of the splitting device through a simple linear regression model; Step 5: Build an intelligent evaluation model through neural network algorithm; Step 6: Evaluate the impact of water flow data and tidal data on the splitting equipment and take appropriate measures.

[0014] Beneficial effects of the invention: Compared with the traditional intelligent control device and method for splitting and clearing reefs, the intelligent control device and method for splitting and clearing reefs in the invention closely combine the monitoring data acquisition technology, neural network algorithm technology and modern information technology, and accurately capture the water flow data, tide data, reef data and splitting equipment working status data through Doppler current meter, radar tide meter, level ruler, level and sensor equipment, and obtain the influence of water source data on the displacement of splitting equipment and the influence of tide data on the water entry depth of splitting equipment through the collaborative working process of monitoring data initial processing module, monitoring indicator module and model building module, so as to achieve the control of splitting and clearing reefs in the process of splitting and clearing reefs. Real-time and comprehensive monitoring of equipment operating status and environmental factors solves the problem that the existing intelligent control devices and methods for splitting and reef clearing are unable to comprehensively analyze multiple factors and control the process of splitting and reef clearing, making it difficult to ensure the accuracy of splitting and reef clearing, affecting the effect of splitting and reef clearing. It ensures that the method in the present invention can refine the dynamic monitoring standards for intelligent control devices and methods for splitting and reef clearing within a more precise range, so that the monitored data becomes a more accurate indicator under the same conditions. The development and application of this method significantly enhances the degree of intelligence in the intelligent control process of splitting and reef clearing, effectively improves the efficiency and quality of reef clearing, and provides more reliable technical support for reef clearing operations in fishing port projects. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in the present invention. For ordinary technicians in this field, other drawings can also be obtained based on these drawings.

[0016] Figure 1 A block diagram of an intelligent control device for splitting and clearing reefs according to the present invention; Figure 2 The present invention is a flow chart of an intelligent control method for splitting and clearing reefs. DETAILED DESCRIPTION

[0017] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0018] Embodiment 1, as Figure 1 As shown, the present invention provides an intelligent control device for splitting and clearing reefs, including a monitoring data acquisition module, a monitoring data initial processing module, a monitoring index module, a model building module and an intelligent evaluation control module; The monitoring data acquisition module uses Doppler current meters, radar tide gauges, leveling rods, level gauges and sensor equipment to collect monitoring data for reef-clearing and splitting, providing data support for subsequent monitoring of reef-clearing operations with splitting equipment; The monitoring data initial processing module pre-processes the monitoring data of splitting and reef clearing, and calculates the real-time displacement of the splitting equipment in all directions in three-dimensional space, providing a guarantee for the smooth progress of subsequent monitoring and evaluation; The monitoring indicator module is divided into a monitoring indicator unit and a monitoring evaluation unit. The monitoring indicator unit is used to obtain the displacement deviation of the splitting equipment and the degree of reef inundation; the monitoring evaluation unit is used to obtain the influence of water flow data on the displacement of the splitting equipment and the influence of tidal data on the depth of the splitting equipment entering the water, which provides data support for building an intelligent evaluation model. Model building module, which builds intelligent evaluation models through neural network algorithms; The intelligent assessment control module evaluates the impact of water flow and tide on the splitting equipment and takes corresponding measures to deal with it, providing a solution to the problem that traditional splitting and reef clearing devices and methods are unable to integrate multiple factors to ensure the accuracy of splitting and reef clearing.

[0019] The monitoring data acquisition module uses Doppler current meters, radar tide gauges, leveling rods, level gauges and sensor equipment to collect reef-breaking monitoring data, including the following processes: The sensors include laser displacement sensors and ultrasonic sensors; The splitting reef clearing monitoring data includes water flow data, tidal data, reef data and splitting equipment working status data, wherein the water flow data is the real-time water flow velocity and its direction; the tidal data is the tide height; the reef data is the top elevation of the reef; the splitting equipment working status data is the real-time three-dimensional displacement coordinate data of the splitting equipment and the water immersion depth of the splitting equipment.

[0020] Monitoring data collection module, the collection process of reef splitting and clearing monitoring data includes: A1. Calibrate the Doppler flow meter. Put the calibrated Doppler flow meter into the water and obtain the real-time water flow velocity based on the Doppler effect. The Doppler flow meter is equipped with a transducer. By measuring the difference in the sound wave frequency received by different transducers, the corresponding water flow direction is calculated. A2. Use the zero-point calibration method to place the radar tide meter in still water and adjust the zero point of the instrument. The calibrated radar tide meter transmits radar waves to the water surface. The radar waves are reflected by the water surface and received by the radar tide meter. According to the transmission and reception time of the radar waves and the propagation speed of the radar waves in the air, the distance between the radar tide meter and the water surface is calculated to obtain the tide height. A3. Fix the level rod vertically on the elevation point. Use the telescope of the level to aim the level rod. Adjust the focusing screw of the objective lens until the image of the level rod is clear. Read the reading on the level rod and record it as the rearsight reading a. Place a ruler pad on the top of the reef, fix the level rod vertically on the ruler pad, aim the level rod through the level, read the reading on the level rod and record it as the foresight reading b. According to the formula h=ab, calculate and obtain the top elevation of the reef. A4. Fix the laser displacement sensor on the splitting device, start the splitting device, output real-time displacement data through the laser displacement sensor, establish a three-dimensional coordinate system according to the structure and movement characteristics of the splitting device, transfer the real-time displacement data output by the laser displacement sensor to the three-dimensional coordinate system, and obtain the real-time three-dimensional displacement coordinate data of the splitting device; A5. Install the ultrasonic sensor on the top of the splitting device in a direction perpendicular to the water surface. Before the splitting device enters the water, measure the initial distance from the ultrasonic sensor to the water surface to obtain the total height H of the splitting device. After the splitting device enters the water, the ultrasonic sensor measures the distance n from the top of the splitting device to the water surface in real time. The real-time water depth m of the splitting device is calculated using the formula m=Hn.

[0021] The monitoring data initial processing module pre-processes the splitting and reef clearing monitoring data and calculates the real-time displacement of the splitting equipment in all directions in three-dimensional space. The process includes: The splitting and reef clearing monitoring data is cleaned, and the real-time three-dimensional displacement coordinate data corresponding to two time points are extracted from the real-time three-dimensional displacement coordinate data of the splitting equipment. The two time points t1 and t2 are recorded, and the process of calculating the real-time displacement of the splitting equipment in all directions in the three-dimensional space is as follows: in, , and are the real-time displacements of the splitting device in the x-axis, y-axis and z-axis directions during the time period t1~t2 respectively; x1 and x2 correspond to the real-time displacements of the splitting device in the x-axis direction at t1 and t2 respectively; y1 and y2 correspond to the real-time displacements of the splitting device in the y-axis direction at t1 and t2 respectively; z1 and z2 correspond to the real-time displacements of the splitting device in the z-axis direction at t1 and t2 respectively.

[0022] The process of monitoring the indicator unit and obtaining the displacement deviation of the splitting equipment and the degree of reef inundation includes: B1. Obtain the real-time displacement components of the splitting equipment in the x, y, and z directions during the time period t1 to t2 through the real-time three-dimensional displacement data of the splitting equipment , , ; According to the direction of water flow, decompose the water flow velocity in the time period t1~t2 to obtain the water flow velocity components in the x, y, and z directions , , , set the theoretical value of water flow velocity , and ,pass = (t2-t1) formula, calculate the theoretical displacement value of the splitting device in the x-axis, y-axis and z-axis directions , , ; Using the theoretical displacement value of the splitting device , calculate the displacement deviation of the splitting device: in, , are the displacement deviations of the splitting equipment in the x-axis, y-axis and z-axis directions, , and are the real-time displacement components of the splitting device in the x-axis, y-axis and z-axis directions during the time period t1 to t2, , and are the theoretical displacement values ​​of the splitting device in the x-axis, y-axis and z-axis directions respectively; B2. The process of calculating the degree of reef inundation is as follows: in, is the degree of reef inundation, is the tide height, is the top elevation of the reef.

[0023] The monitoring and evaluation unit obtains the influence of water flow data on the displacement of the splitting equipment through the following process: Combined with the theoretical displacement values ​​and displacement deviations of the splitting equipment in the x-axis, y-axis and z-axis directions, the influence of the water flow data on the displacement of the splitting equipment is calculated: in, , and are the influence of water flow data on the displacement of the splitting equipment in the x-axis, y-axis and z-axis directions, respectively. , , are the theoretical displacements of the splitting device in the x-axis, y-axis and z-axis directions, , are the displacement deviations of the splitting equipment in the x-axis, y-axis and z-axis directions respectively.

[0024] The monitoring and evaluation unit obtains the influence of tidal data on the water depth of the splitting equipment, including: The degree of reef submergence in time period i is obtained by calculation and is set as ; Extract the water entry depth data of the splitting equipment corresponding to the i time period from the real-time water entry depth data of the splitting equipment collected, and set it as ; Selecting a simple linear regression model in, Provide real-time water depth data for splitting equipment; is the degree of reef inundation, is the intercept, is the regression coefficient and represents the influence of tide data on the water depth of the splitting equipment. is the error term; Using the least squares method, calculate The process is:

[0025] in, and are the average values ​​of the reef submergence degree and the water entry depth of the splitting equipment in time period i; is the reef submergence degree in time period i, is the water entry depth data of the splitting equipment in the i time period, where c=1,2,3...i; is the regression coefficient, which indicates the influence of tidal data on the water entry depth of the splitting equipment.

[0026] The model building module uses a neural network algorithm to build an intelligent evaluation model. The process includes: The neural network architecture includes an input layer, a hidden layer and an output layer. Two neurons are set in the input layer, and the two neurons receive water flow data and tidal data respectively as the input of the neural network; two hidden layers are set, and a Batch Normalization layer is added between the hidden layers to normalize the data of each layer; two neurons are set in the output layer, which respectively output the influence of water source data on the displacement of the splitting equipment and the influence of tidal data on the water entry depth of the splitting equipment; A neural network model was constructed, and the water source data and its influence on the displacement of the splitting equipment, and the tidal data and its influence on the water depth of the splitting equipment were used as data sets. The data sets were divided into a training set and a validation set in a ratio of 8:2. The training set data is input into the neural network model. Through forward propagation, the training set data is passed through the neural network layer by layer. Each layer performs weighted summation on the training set data to obtain the prediction result of the output layer. Then, through back propagation, the error between the prediction result of the output layer and the actual result is back propagated to update the weights and configuration of the network and obtain a preliminary neural network model. The performance of the preliminary neural network model was evaluated using the validation set, the model parameters were adjusted, the model was optimized, the error of the output results was reduced, and the neural network model with adjusted parameters was deployed to the reef splitting and clearing intelligent control device to obtain the intelligent evaluation model.

[0027] The intelligent evaluation control module evaluates the impact of water flow data and tidal data on the splitting equipment and takes corresponding measures to deal with the process including: The water source data is input into the intelligent assessment model. When the influence of the water source data on the displacement of the splitting equipment is less than 30%, it means that the water source data has a slight impact on the splitting and reef clearing process, and the regular monitoring of the water flow data should be maintained; when the influence of the water source data on the displacement of the splitting equipment is between 30% and 50%, it means that the water source data has a moderate impact on the splitting and reef clearing process, and the splitting equipment should be equipped with additional fixed ropes and reinforced support structures; when the influence of the water source data on the displacement of the splitting equipment is greater than 50%, it means that the water source data has a severe impact on the splitting and reef clearing process, and the splitting and reef clearing operation should be stopped, the splitting equipment should be fully inspected, repaired and reinforced, and an early warning signal should be issued; The tidal data is input into the intelligent assessment model. When the influence of tidal data on the water entry depth of the splitting equipment is less than 30%, it means that the tidal data has a slight impact on the splitting and reef clearing process, and regular monitoring of tidal data should be maintained; when the influence of tidal data on the water entry depth of the splitting equipment is between 30% and 50%, it means that the tidal data has a moderate impact on the splitting and reef clearing process, and the splitting angle and force should be adjusted to control the water entry depth of the splitting equipment; when the influence of tidal data on the water entry depth of the splitting equipment is higher than 50%, it means that the tidal data has a severe impact on the splitting and reef clearing process, and the splitting and reef clearing operation should be stopped, the splitting equipment should be comprehensively inspected, and an early warning signal should be issued.

[0028] Embodiment 2, as Figure 2 As shown, based on Example 1, the present invention provides a technical solution: an intelligent control method for splitting and clearing reefs, which is used to implement the above-mentioned intelligent control device for splitting and clearing reefs, and is composed of the following steps: Step 1: Use a Doppler current meter and a radar tide meter to collect real-time water flow velocity, water flow direction and tide height, use a level ruler and a level to collect the top elevation of the reef, and use a laser displacement sensor and an ultrasonic sensor to collect real-time three-dimensional displacement coordinate data of the splitting equipment and the real-time water entry depth of the splitting equipment; Step 2: Perform data cleaning on the real-time water flow velocity, water flow direction, tide height, real-time three-dimensional displacement coordinate data of the splitting equipment and the real-time water entry depth of the splitting equipment, and calculate the real-time displacement of the splitting equipment in each direction of the three-dimensional space; Step 3: Calculate the theoretical displacement value of the splitting device in all directions of the three-dimensional space by using the water flow velocity and water flow direction, and then obtain the displacement deviation of the splitting device by combining the real-time displacement of the splitting device in all directions of the three-dimensional space; calculate the submergence degree of the reef by using the tide height and the top elevation of the reef; Step 4: Calculate the influence of water flow data on the displacement of the splitting device using the theoretical displacement and displacement deviation of the splitting device in the x-axis, y-axis and z-axis directions; obtain the influence of tidal data on the water entry depth of the splitting device through a simple linear regression model; Step 5: Build an intelligent evaluation model through neural network algorithm; Step 6: Evaluate the impact of water flow data and tidal data on the splitting equipment and take appropriate measures.

[0029] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

Claims

1. The intelligent control device for splitting and clearing reefs includes a monitoring data acquisition module, a monitoring data initial processing module, a monitoring index module, a model building module and an intelligent evaluation control module, and is characterized by: The monitoring data acquisition module collects the reef-breaking and reef-clearing monitoring data using a Doppler current meter, a radar tide gauge, a leveling ruler, a level and sensor equipment; The monitoring data initial processing module pre-processes the splitting and reef clearing monitoring data and calculates the real-time displacement of the splitting equipment in all directions in the three-dimensional space; The monitoring indicator module is divided into a monitoring indicator unit and a monitoring evaluation unit, wherein the monitoring indicator unit is used to obtain the displacement deviation of the splitting equipment and the degree of reef submergence; the monitoring evaluation unit is used to obtain the influence of water flow data on the displacement of the splitting equipment and the influence of tidal data on the water entry depth of the splitting equipment; The model building module builds an intelligent evaluation model through a neural network algorithm; The intelligent evaluation control module evaluates the influence of water flow and tide on the splitting equipment and takes corresponding measures to deal with it.

2. The intelligent control device for splitting and clearing reefs according to claim 1 is characterized in that: The monitoring data acquisition module collects the reef-breaking and reef-clearing monitoring data by using a Doppler current meter, a radar tide gauge, a level ruler, a level meter and sensor equipment, including: The sensors include laser displacement sensors and ultrasonic sensors; The splitting reef clearing monitoring data includes water flow data, tidal data, reef data and splitting equipment working status data, wherein the water flow data is the real-time water flow velocity and its direction; the tidal data is the tide height; the reef data is the top elevation of the reef; the splitting equipment working status data is the real-time three-dimensional displacement coordinate data of the splitting equipment and the water immersion depth of the splitting equipment.

3. The intelligent control device for splitting and clearing reefs according to claim 2 is characterized in that: The monitoring data collection module includes the following steps: A1. Calibrate the Doppler flow meter. Put the calibrated Doppler flow meter into the water and obtain the real-time water flow velocity based on the Doppler effect. The Doppler flow meter is equipped with a transducer. By measuring the difference in the sound wave frequency received by different transducers, the corresponding water flow direction is calculated. A2. Use the zero-point calibration method to place the radar tide meter in still water and adjust the zero point of the instrument. The calibrated radar tide meter transmits radar waves to the water surface. The radar waves are reflected by the water surface and received by the radar tide meter. According to the transmission and reception time of the radar waves and the propagation speed of the radar waves in the air, the distance between the radar tide meter and the water surface is calculated to obtain the tide height. A3. Fix the level rod vertically on the elevation point. Use the telescope of the level to aim the level rod. Adjust the focusing screw of the objective lens until the image of the level rod is clear. Read the reading on the level rod and record it as the rearsight reading a. Place a ruler pad on the top of the reef, fix the level rod vertically on the ruler pad, aim the level rod through the level, read the reading on the level rod and record it as the foresight reading b. According to the formula h=ab, calculate and obtain the top elevation of the reef. A4. Fix the laser displacement sensor on the splitting device, start the splitting device, output real-time displacement data through the laser displacement sensor, establish a three-dimensional coordinate system according to the structure and movement characteristics of the splitting device, transfer the real-time displacement data output by the laser displacement sensor to the three-dimensional coordinate system, and obtain the real-time three-dimensional displacement coordinate data of the splitting device; A5. Install the ultrasonic sensor on the top of the splitting device in a direction perpendicular to the water surface. Before the splitting device enters the water, measure the initial distance from the ultrasonic sensor to the water surface to obtain the total height H of the splitting device. After the splitting device enters the water, the ultrasonic sensor measures the distance n from the top of the splitting device to the water surface in real time. The real-time water depth m of the splitting device is calculated using the formula m=Hn.

4. The intelligent control device for splitting and clearing reefs according to claim 3 is characterized in that: The monitoring data initial processing module pre-processes the splitting and reef clearing monitoring data and calculates the real-time displacement of the splitting equipment in all directions in the three-dimensional space. The process includes: The splitting and reef clearing monitoring data is cleaned, and the real-time three-dimensional displacement coordinate data corresponding to two time points are extracted from the real-time three-dimensional displacement coordinate data of the splitting equipment. The two time points t1 and t2 are recorded, and the process of calculating the real-time displacement of the splitting equipment in all directions in the three-dimensional space is as follows: in, , and are the real-time displacements of the splitting device in the x-axis, y-axis and z-axis directions during the time period t1~t2 respectively; x1 and x2 correspond to the real-time displacements of the splitting device in the x-axis direction at t1 and t2 respectively; y1 and y2 correspond to the real-time displacements of the splitting device in the y-axis direction at t1 and t2 respectively; z1 and z2 correspond to the real-time displacements of the splitting device in the z-axis direction at t1 and t2 respectively.

5. The intelligent control device for splitting and clearing reefs according to claim 4 is characterized in that: The monitoring indicator unit, the process of obtaining the displacement deviation of the splitting equipment and the degree of reef submergence includes: B1. Obtain the real-time displacement components of the splitting equipment in the x, y, and z directions during the time period t1 to t2 through the real-time three-dimensional displacement data of the splitting equipment , , ; According to the direction of water flow, decompose the water flow velocity in the time period t1~t2 to obtain the water flow velocity components in the three directions of x, y, and z , , , set the theoretical value of water flow velocity , and ,pass = (t2-t1) formula, calculate the theoretical displacement value of the splitting device in the x-axis, y-axis and z-axis directions , , ; Using the theoretical displacement value of the splitting device , calculate the displacement deviation of the splitting device: in, , are the displacement deviations of the splitting equipment in the x-axis, y-axis and z-axis directions, , and are the real-time displacement components of the splitting device in the x-axis, y-axis and z-axis directions during the time period t1 to t2, , and are the theoretical displacement values ​​of the splitting device in the x-axis, y-axis and z-axis directions respectively; B2. The process of calculating the degree of reef inundation is as follows: in, is the degree of reef inundation, is the tide height, is the top elevation of the reef.

6. The intelligent control device for splitting and clearing reefs according to claim 5 is characterized in that: The process of obtaining the influence of water flow data on the displacement of the splitting device by the monitoring and evaluation unit includes: Combined with the theoretical displacement values ​​and displacement deviations of the splitting equipment in the x-axis, y-axis and z-axis directions, the influence of the water flow data on the displacement of the splitting equipment is calculated: in, , and are the influence of water flow data on the displacement of the splitting equipment in the x-axis, y-axis and z-axis directions, respectively. , , are the theoretical displacements of the splitting device in the x-axis, y-axis and z-axis directions, , are the displacement deviations of the splitting equipment in the x-axis, y-axis and z-axis directions respectively.

7. The intelligent control device for splitting and clearing reefs according to claim 6 is characterized in that: The process of obtaining the influence of tidal data on the water entry depth of the splitting equipment by the monitoring and evaluation unit includes: The degree of reef submergence in time period i is obtained by calculation and is set as ; Extract the water depth data of the splitting equipment corresponding to the i time period from the real-time water depth data of the splitting equipment collected, and set it as ; Selecting a simple linear regression model in, Provide real-time water depth data for splitting equipment; is the degree of reef inundation, is the intercept, is the regression coefficient and represents the influence of tide data on the water depth of the splitting equipment. is the error term; Using the least squares method, calculate The process is: in, and are the average values ​​of the reef submergence degree and the water entry depth of the splitting equipment in time period i; is the reef submergence degree in time period i, is the water entry depth data of the splitting equipment in the i time period, where c=1,2,3...i; is the regression coefficient, which indicates the influence of tidal data on the water entry depth of the splitting equipment.

8. The intelligent control device for splitting and clearing reefs according to claim 7 is characterized in that: The model building module, through the neural network algorithm, builds an intelligent evaluation model, including: The neural network architecture includes an input layer, a hidden layer and an output layer. Two neurons are set in the input layer, and the two neurons receive water flow data and tidal data respectively as the input of the neural network; two hidden layers are set, and a Batch Normalization layer is added between the hidden layers to normalize the data of each layer; two neurons are set in the output layer, which respectively output the influence of water source data on the displacement of the splitting equipment and the influence of tidal data on the water entry depth of the splitting equipment; A neural network model was constructed, and the water source data and its influence on the displacement of the splitting equipment, and the tidal data and its influence on the water depth of the splitting equipment were used as data sets. The data sets were divided into a training set and a validation set in a ratio of 8:

2. The training set data is input into the neural network model. Through forward propagation, the training set data is passed through the neural network layer by layer. Each layer performs weighted summation on the training set data to obtain the prediction result of the output layer. Then, through back propagation, the error between the prediction result of the output layer and the actual result is back propagated to update the weights and configuration of the network and obtain a preliminary neural network model. The performance of the preliminary neural network model was evaluated using the validation set, the model parameters were adjusted, the model was optimized, the error of the output results was reduced, and the neural network model with adjusted parameters was deployed to the reef splitting and clearing intelligent control device to obtain the intelligent evaluation model.

9. The intelligent control device for splitting and clearing reefs according to claim 8 is characterized in that: The process of the intelligent evaluation control module evaluating the influence of water flow data and tidal data on the splitting equipment and taking corresponding measures to deal with the influence includes: The water source data is input into the intelligent assessment model. When the influence of the water source data on the displacement of the splitting equipment is less than 30%, it means that the water source data has a slight impact on the splitting and reef clearing process, and the regular monitoring of the water flow data should be maintained; when the influence of the water source data on the displacement of the splitting equipment is between 30% and 50%, it means that the water source data has a moderate impact on the splitting and reef clearing process, and the splitting equipment should be equipped with additional fixed ropes and reinforced support structures; when the influence of the water source data on the displacement of the splitting equipment is greater than 50%, it means that the water source data has a severe impact on the splitting and reef clearing process, and the splitting and reef clearing operation should be stopped, the splitting equipment should be fully inspected, repaired and reinforced, and an early warning signal should be issued; The tidal data is input into the intelligent assessment model. When the influence of tidal data on the water entry depth of the splitting equipment is less than 30%, it means that the tidal data has a slight impact on the splitting and reef clearing process, and regular monitoring of tidal data should be maintained; when the influence of tidal data on the water entry depth of the splitting equipment is between 30% and 50%, it means that the tidal data has a moderate impact on the splitting and reef clearing process, and the splitting angle and force should be adjusted to control the water entry depth of the splitting equipment; when the influence of tidal data on the water entry depth of the splitting equipment is higher than 50%, it means that the tidal data has a severe impact on the splitting and reef clearing process, and the splitting and reef clearing operation should be stopped, the splitting equipment should be comprehensively inspected, and an early warning signal should be issued.

10. A method for intelligent control of reef splitting and clearing, implemented based on the intelligent control device for reef splitting and clearing as claimed in any one of claims 1 to 9, characterized in that: It consists of the following steps: Step 1: Use a Doppler current meter and a radar tide meter to collect real-time water flow velocity, water flow direction and tide height, use a level ruler and a level to collect the top elevation of the reef, and use a laser displacement sensor and an ultrasonic sensor to collect real-time three-dimensional displacement coordinate data of the splitting equipment and the real-time water entry depth of the splitting equipment; Step 2: Perform data cleaning on the real-time water flow velocity, water flow direction, tide height, real-time three-dimensional displacement coordinate data of the splitting equipment and the real-time water entry depth of the splitting equipment, and calculate the real-time displacement of the splitting equipment in each direction of the three-dimensional space; Step 3: Calculate the theoretical displacement value of the splitting device in all directions of the three-dimensional space by using the water flow velocity and water flow direction, and then obtain the displacement deviation of the splitting device by combining the real-time displacement of the splitting device in all directions of the three-dimensional space; calculate the submergence degree of the reef by using the tide height and the top elevation of the reef; Step 4: Calculate the influence of water flow data on the displacement of the splitting device using the theoretical displacement and displacement deviation of the splitting device in the x-axis, y-axis and z-axis directions; obtain the influence of tidal data on the water entry depth of the splitting device through a simple linear regression model; Step 5: Build an intelligent evaluation model through neural network algorithm; Step 6: Evaluate the impact of water flow data and tidal data on the splitting equipment and take appropriate measures.

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