Marine sand excavation monitoring system and method

Abstract

The invention discloses a marine sand excavation monitoring system and method which are used for solving the problems that an existing marine sand excavation monitoring system is insufficient in monitoring precision and insufficient in environmental change early warning. Comprising a monitoring acquisition module, an environment monitoring analysis module, a precision monitoring analysis module and an execution module. According to the method, environmental factors and the precision of sand excavation equipment are monitored and analyzed in real time, the influence of sand excavation activities on the environment is effectively evaluated, the environmental quality influence coefficient and the environmental state influence coefficient are calculated, adjustment is conducted in combination with dynamic environmental data, environmental changes are found in time, and the negative influence of sand excavation on the ecological environment is reduced; the precision deviation of the equipment is automatically analyzed through a precision monitoring and correction module, and dynamic correction is performed according to a correlation analysis result, so that the equipment always runs in a high-precision range; the accurate control mode optimizes the sand excavation process, improves the sand excavation efficiency and the resource utilization rate, and meanwhile reduces operation errors and environment disturbance.

Description

Technical Field

[0001] The present invention relates to the technical field of marine sand mining monitoring, and specifically provides a marine sand mining monitoring system and method. Background Art

[0002] Marine sand mining monitoring systems mainly rely on remote sensing technology, satellite monitoring, automated sensors, and data analysis platforms to achieve real-time monitoring of marine sand mining activities. These systems can collect environmental data related to sand mining, such as water depth, flow rate, temperature, salinity, sand composition, etc., and use technologies such as seabed topography scanning, ship positioning, and video monitoring to accurately track the sand mining operation area. However, existing systems still face a series of problems: insufficient monitoring accuracy: Although remote sensing technology and sensors can provide a large amount of data, in complex marine environments, especially in deep sea areas, the resolution and accuracy of sensors are often insufficient, resulting in unsatisfactory monitoring effects of sand mining activities; insufficient early warning of environmental changes: Due to the lack of an effective environmental change prediction mechanism, existing systems are difficult to early warn of abnormal fluctuations in the marine environment, such as changes in water temperature, flow rate, etc., which may have potential impacts on the ecological environment and sand mining operations. Summary of the Invention

[0003] The purpose of the present invention is to propose a marine sand mining monitoring system and method to solve the above existing problems.

[0004] The purpose of the present invention can be achieved through the following technical solutions: A marine sand mining monitoring system includes an environmental monitoring and analysis module and an accuracy monitoring and analysis module;

[0005] The environmental monitoring and analysis module is used to analyze environmental data, specifically:

[0006] Analyze environmental quality data to obtain the ideal value corresponding to each environmental factor under the ideal environmental state of the acquisition area. According to the results collected by the monitoring and acquisition module, collect the current environmental factor values, calculate the deviation degree of the environmental factors, and obtain the deviation degree D of the i-th environmental factor i ; Standardize each deviation value to make it on a unified scale through the established formula: Output the environmental quality impact coefficient HZZ, where ω i is the weight of the i-th factor, and D i ' is the standardized deviation value of the i-th environmental factor;

[0007] Analyze environmental state data to obtain the environmental state impact coefficient E(x, y, z, t);

[0008] The accuracy monitoring and analysis module is used to analyze the sand mining accuracy of sand mining equipment, specifically:

[0009] Obtain the sand mining area, analyze the seabed topography, and preprocess the topographic data to obtain the slope S between the j-th and the (j + 1)-th points j , then extract several contour lines from the topographic data. After the contour lines are extracted, select a suitable path according to the characteristics of the equipment; first calculate the slope to obtain the slope S;

[0010] Obtain the deviation between the current position and the ideal position of the equipment; the actual collection point of the sand mining equipment is (x j ', y j ', z j '), while the ideal collection point is (x0, y0, z0). Then, the accuracy deviation value of the equipment at this position is calculated through the established formula: Output the accuracy deviation value D of the j-th point j , and then calculate the average deviation value and the maximum deviation value of the sand mining equipment in the entire area; through the formula: Output the average deviation value Dp, Dmax = max(D1, D2,..., D m ) Output the maximum deviation value Dmax; then analyze the correlation between the accuracy and the environmental quality impact coefficient HZZ and the environmental state impact coefficient E(x, y, z, t) to obtain the Spearman rank correlation coefficients r1 and r2.

[0011] As a preferred embodiment of the present invention, it further includes a monitoring and acquisition module and an execution module;

[0012] The monitoring and acquisition module is used to collect monitoring data during the marine sand mining process. The monitoring data includes environmental data, accuracy data, and compliance data; among them, the environmental data includes environmental quality data and environmental state data. The environmental quality data includes water quality, bottom sediment, and climate; the environmental state data includes water flow velocity, temperature, and depth; the accuracy data includes position, operation parameters, and equipment status data; the compliance data includes operation area, compliance with laws and regulations, and environmental impact assessment;

[0013] The execution module is used to obtain the corrected accuracy deviation value D' to generate equipment correction instructions one and two and execute equipment correction.

[0014] As a preferred embodiment of the present invention, the specific process of obtaining the deviation degree D of the i-th environmental factor i is as follows:

[0015] Compare the difference between the current value and the ideal value of each environmental factor to quantify the impact of sand mining activities on the environment. From the formula: D i = |X i - X iL | Output the deviation degree D of the i-th environmental factor i , X iis the current acquisition value of the i-th environmental factor, X iL is the ideal value of the i-th environmental factor.

[0016] As a preferred embodiment of the present invention, the specific process of obtaining the environmental state influence coefficient E(x, y, z, t) is as follows:

[0017] Calculate the water flow velocity factor, collect water flow velocity and direction data at different positions (x, y, z), and record the time series. Calculate the displacement of the water flow in space according to the monitored flow velocity V and time interval Δt: S(x, y, z, t) = V(x, y, z, t) × Δt; the cross-sectional area represents the cross-sectional area perpendicular to the water flow direction at a certain spatial position; measure the river depth (z) and width at the specified position (x, y) through a hydrological section instrument; draw a cross-sectional profile, divide the profile into small units, and sum to obtain the cross-sectional area A(x, y, z); through the established formula: Output the flow velocity V at the spatial position (x, y, z) and time t LS (x, y, z, t), is the partial derivative, which changes with different time t and spatial positions (x, y, z);

[0018] Calculate the temperature factor to obtain the time change rate of temperature Calculate the depth factor to obtain the water depth Ds(x, y, t); through the established formula:

[0019]

[0020] Output the environmental state influence coefficient E(x, y, z, t), is the convective term of the water flow on the temperature change, the water depth change ΔDc(x, y, t), and a1, a2, a3, and a4 are all preset weights.

[0021] As a preferred embodiment of the present invention, the specific process of calculating the temperature factor to obtain the time change rate of temperature is as follows:

[0022] Through the established formula: Output the time change rate of temperature where α is the preset water body heat diffusion value, represents the spatial second-order gradient of temperature, is the convective term of the water flow on the temperature change, and Q1 is the influence of the external heat source.

[0023] As a preferred embodiment of the present invention, the specific process of calculating the depth factor to obtain the water depth Ds(x, y, t) is as follows:

[0024] The change in the depth factor is caused by tidal and sand mining activities. Among them, the tidal change ΔDc(t2) is represented by a sine function: Output the tidal change ΔDc(t2), where Ac is the tidal amplitude, θ is the angular frequency of the tide, t is the time variable, and φ is the phase shift of the tide; the water depth change ΔDc(x, y, t) caused by human activities is obtained through the established formula: Output the water depth change ΔDc(x, y, t), where Vc(x, y, t) is the volume of sand removed by sand mining activities at a certain position (x, y) and time t, and Ac(x, y) is the cross-sectional area of the water body corresponding to the sand mining area; output the water depth Ds(x, y, t) at a certain position (x, y) at time t in the dynamic environment through the established formula: Ds(x, y, t) = D0(x, y) + ΔDc(t2) + ΔDc(x, y, t), where D0(x, y) is the initial water depth.

[0025] As a preferred embodiment of the present invention, the specific process of calculating the slope to obtain the slope S is as follows:

[0026] The terrain data is: Bd = {(x1, y1, z1), (x1, y1, z1), …, (x m , y m , z m )}, where (x j , y j , z j ) represents the coordinates of the j-th measurement point, and z j is the seabed depth at this point; connect each adjacent two data points in the terrain data to obtain a seabed terrain network diagram; calculate the slope of the seabed terrain network diagram through the established formula: Output the slope S between the j-th and the (j + 1)-th points j ; z j+1 , z j are the depths of adjacent points, and (x j+1 , x j ) and (y j+1 , y j ) are the coordinates of adjacent points;

[0027] Extract several contour lines from the terrain data, and select one contour line for each depth interval; in the plane coordinate system (x, y), extract all points with the same depth according to the given depth value, and connect them into a contour line. For each contour line, it is subdivided into multiple small segments according to its adjacent depth values and slope changes, and each small segment will be used as a path segment for the sand mining equipment; after the contour lines are extracted, select a suitable path according to the characteristics of the equipment; calculate the slope: obtain the slope S through the established formula, and compare the slope S with the corresponding slope threshold. If the slope S is less than the corresponding threshold, this area is more suitable for the stable operation of the equipment; otherwise, optimize the path, use the curve fitting method to smooth the path, and divide the path into several small segments.

[0028] As a preferred embodiment of the present invention, the specific process of obtaining the Spearman rank correlation coefficients r1 and r2 is as follows:

[0029] There are k calculation samples, and the data includes the accuracy deviation value D, the environmental quality impact coefficient HZZ, and the environmental state impact coefficient E(x, y, z, t); sort the data by numerical size and assign ranks. If there are equal values, take the average rank; calculate the difference in ranks of the two variables corresponding to each sample. Find the square d h 1 2 , d h 2 2 For all d h 1 2 , d h 2 2 Add them up to get ∑d h 1 2 , ∑d h 2 2 ; Substitute the calculated data into the formula: Output the Spearman rank correlation coefficients r1 and r2; the Spearman rank correlation coefficient r1 is the correlation coefficient with the environmental quality impact coefficient HZZ, and the Spearman rank correlation coefficient r2 is the correlation coefficient with the environmental state impact coefficient E(x, y, z, t); if r1 > 0 or r2 > 0, it is a positive correlation, which means that when the environmental factors increase, the accuracy deviation value D increases. If r1 < 0 or r2 < 0, it is a negative correlation, which means that when the environmental factors increase, the accuracy deviation value D decreases;

[0030] The accuracy deviation value D is corrected through the correlation between them: through the established correction formula: D' = D - β1×HZZ - β2×E(x,y,z,t), the corrected accuracy deviation value D' is output. β1 is the correction factor related to r1, and β2 is the correction factor related to r2; the correction factors α1 and β2 are obtained through the established formula: β1 = u1×|r1|, β2 = u2×|r2|, where u1 and u2 are preset weight factors; |r1| and |r2| are the absolute values of the Spearman rank correlation coefficients; if the corrected accuracy deviation value D', D' ≤ 0.5 m, no equipment correction is required. If the corrected accuracy deviation value D', 0.5 < D' ≤ 1.0 m, equipment correction instruction one is generated; if the corrected accuracy deviation value D', D' > 1.0 m, equipment correction instruction two is generated.

[0031] A marine sand mining monitoring method is applied to implement any one of the marine sand mining monitoring systems of claims 1-8. The method includes:

[0032] Step 1: The monitoring and acquisition module collects environmental data, accuracy data, and compliance data;

[0033] Step 2: The environmental monitoring and analysis module calculates the deviation degree of environmental factors, and calculates the environmental quality impact coefficient through standardization processing and weight assignment;

[0034] Step 3: Calculate the dynamic factors of water flow velocity, temperature, and depth, and output the environmental state impact coefficient;

[0035] Step 4: The accuracy monitoring and analysis module calculates the accuracy deviation value of the equipment, and evaluates the equipment accuracy level according to the correlation analysis between the environmental impact coefficient and the accuracy deviation;

[0036] Step 5: Calculate the correction factor according to the deviation value and correlation analysis, and generate equipment correction instruction one and equipment correction instruction two;

[0037] Step 6: The execution module adjusts the equipment coordinates, speed, path, and operation depth according to the correction instruction to ensure that the equipment accuracy meets the requirements.

[0038] Compared with the prior art, the beneficial effects of the present invention are:

[0039] 1. The present invention can analyze and evaluate the environmental impact of sand mining activities in real time to ensure that the operations comply with ecological protection standards. By monitoring environmental factors such as water quality, sediment quality, and ecological impact, and combining with the ideal values of each factor, the system can quantify the degree of deviation of the current environmental state and standardize it. By calculating the environmental quality impact coefficient and the environmental state impact coefficient, the system can determine whether the current environmental quality meets the sand mining conditions. If the environmental quality impact coefficient exceeds the preset execution range, the system will automatically prevent the sand mining activity to avoid adverse effects on the environment. This dynamic monitoring ensures that the sand mining process is always carried out within the environmental protection framework, effectively reducing ecological damage.

[0040] 2. The precision monitoring and analysis module of the present invention ensures the efficient operation of the sand mining equipment through precise path selection and equipment position adjustment. It tracks the deviation between the actual collection point and the ideal collection point of the equipment in real time and calculates the precision deviation value. According to the Spearman rank correlation coefficient, the system can analyze the relationship between the precision deviation and the environmental quality and state, so as to adjust the equipment operation. When the precision deviation value exceeds the set threshold, the system will generate a correction instruction to reduce the deviation by adjusting the equipment position and speed. Through this automatic precision correction, the sand mining equipment can continuously maintain within the preset precision range, reduce errors, improve the sand mining efficiency, and ensure the minimum interference to the seabed environment during the operation. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] For the convenience of those skilled in the art to understand, the present invention will be further described below in conjunction with the accompanying drawings.

[0042] Figure 1 is the principle block diagram of the present invention;

[0043] Figure 2 is the method step diagram of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0044] The technical solutions of the present invention will be clearly and completely described below in conjunction with the embodiments. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0045] It should be understood that the terms "including" and "comprising" used in the specification and claims of this disclosure indicate the presence of the described features, wholes, steps, operations, elements, and / or components, but do not exclude the presence or addition of one or more other features, wholes, steps, operations, elements, components, and / or their combinations.

[0046] It should also be understood that the terms used in this disclosure statement are for the purpose of describing specific embodiments only and are not intended to limit the disclosure. As used in this disclosure statement and the claims, unless the context clearly indicates otherwise, the singular forms "a", "an", and "the" are intended to include the plural forms. It should also be further understood that the term "and / or" used in this disclosure statement and the claims refers to any combination and all possible combinations of one or more of the associated listed items, and includes these combinations.

[0047] Please refer to Figure 1 As shown, on the one hand, the present invention provides an offshore sand mining monitoring system, including: a monitoring and acquisition module, an environmental monitoring and analysis module, an accuracy monitoring and analysis module, and an execution module;

[0048] The monitoring and acquisition module is used to collect monitoring data during the offshore sand mining process. The monitoring data mainly includes environmental data, accuracy data, compliance data, etc.; among them, the environmental data includes environmental quality data and environmental state data. The environmental quality data includes water quality, bottom sediment, climate, etc.; the environmental state data includes water flow velocity, temperature, depth, etc., data reflecting the health of the ecological environment and the impact of sand mining on the environment, and to ensure the precise execution of sand mining operations, the accuracy data includes location, operation parameters, and equipment status data, to ensure the precise execution of sand mining operations, and the compliance data includes operation areas, legal and regulatory compliance, and environmental impact assessment, etc., to ensure that sand mining activities comply with all relevant regulations;

[0049] The environmental monitoring and analysis module is used to analyze the environmental data, specifically:

[0050] Analyze the environmental quality data: Obtain the ideal value corresponding to each environmental factor under the ideal environmental state of the acquisition area (the ideal value is the best numerical value of the environmental factor in a healthy or ideal state). For example: for the water quality factor: the ideal value is a clear water body (low turbidity, high dissolved oxygen, etc.); for the bottom sediment factor: the ideal value is the original bottom sediment type, and the bottom sediment disturbance is small; for the ecological impact factor: the ideal value is a rich biological population and species diversity;

[0051] According to the results collected by the monitoring and acquisition module, collect the current environmental factor values, such as the current water quality turbidity, dissolved oxygen concentration, etc.; calculate the deviation degree of the environmental factor: compare the current value of each environmental factor with its ideal value, quantify the impact of sand mining activities on the environment, and use the formula: D i =|X i -X iL | to output the deviation degree D of the i-th environmental factor i , where, X i is the current acquisition value of the i-th environmental factor, and X iL is the ideal value of the i-th environmental factor;

[0052] Due to the different dimensions and numerical ranges of different environmental factors, it is necessary to standardize each deviation value so that it is on a unified scale (such as 0 to 1), and then assign a weight value to each environmental factor to reflect the relative importance of the factor to the overall environmental impact, and the sum of the weights is 1;

[0053] Through the established formula: Output the environmental quality impact coefficient HZZ, where ω i is the weight of the i-th factor, and D i ' is the standardized deviation value of the i-th environmental factor; match the calculated environmental quality impact coefficient HZZ with the preset execution range, and the preset execution range includes execution range one and execution range two; if the environmental quality impact coefficient HZZ belongs to execution range one, analyze the environmental status data; if the environmental quality impact coefficient HZZ belongs to execution range two, sand mining cannot be carried out;

[0054] Analyze the environmental status data:

[0055] Calculate the water flow velocity factor. The dynamic change of the water flow velocity factor is determined by the position function and cross-sectional area of the water body passing through the cross-section; the position function of the cross-section is obtained by arranging multi-point sensors (such as current meters, acoustic Doppler current profilers ADCP) in the water body; collect the water flow velocity and direction data at different positions (x, y, z), and record the time series, and calculate the displacement of the water flow in space according to the monitored flow velocity V and time interval Δt: S(x, y, z, t) = V(x, y, z, t) × Δt; the cross-sectional area represents the cross-sectional area perpendicular to the water flow direction at a certain spatial position; by using hydrological section instruments (such as echo sounders), measure the river depth (z) and width at the specified position (x, y); draw a cross-sectional profile, divide the profile into small units (such as triangles or rectangles), and sum to obtain the cross-sectional area A(x, y, z); through the established formula: Output the flow velocity V LS (x, y, z, t), is the partial derivative, which changes with different time t and spatial positions (x, y, z);

[0056] Calculate the temperature factor. The temperature factor is controlled by the heat conduction equation and the water body convection effect. Through the established formula: Output the time change rate of the temperature where α is the preset water body heat diffusion value, represents the second-order spatial gradient of the temperature, is the convection term of the water flow with respect to temperature change, and Q1 is the influence value of an external heat source (such as sunlight heating or industrial waste heat), the magnitude of which is custom - set by those skilled in the art according to actual use;

[0057] Calculate the depth factor. The change of the depth factor is caused by tides and sand - mining activities. Among them, the tidal change ΔDc(t2) is represented by a sine function: Output the tidal change ΔDc(t2). Ac is the tidal amplitude, representing the maximum water - depth change of the ebb and flow of the tide. θ is the angular frequency of the tide (related to the tidal period), t is the time variable used to describe the dynamic change of the tide over time, and φ is the phase shift of the tide, which determines the starting moment of the tide; The water - depth change ΔDc(x, y, t) caused by human activities is obtained through the established formula: Output the water - depth change ΔDc(x, y, t). Vc(x, y, t) is the volume of sand removed by the sand - mining activity at a certain position (x, y) and time t, and Ac(x, y) is the cross - sectional area of the water body corresponding to the sand - mining area;

[0058] Finally, through the established formula: Ds(x, y, t) = D0(x, y)+ΔDc(t2)+ΔDc(x, y, t), output the water depth Ds(x, y, t) at a certain position (x, y) in the dynamic environment at time t. D0(x, y) is the initial water depth, representing the basic water depth of this position without external interference, which is usually determined by the terrain and the original state of the water body; Match the calculated water depth Ds(x, y, t) with the preset operating depth range of the sand - mining equipment. If the water depth Ds(x, y, t) does not belong to the preset operating depth range of the sand - mining equipment, then replace the sand - mining equipment; on the contrary, if the water depth Ds(x, y, t) belongs to the preset operating depth range of the sand - mining equipment, then perform further calculations: Integrate all dynamic factors into a comprehensive dynamic environment index in a weighted manner through the established formula: Output the environmental - state influence coefficient E(x, y, z, t). a1, a2, a3, and a4 are all preset weights, which are adjusted by those skilled in the art according to actual needs;

[0059] The precision - monitoring and analysis module is used to analyze the sand - mining precision of the sand - mining equipment. Specifically:

[0060] Obtain the sand - mining area and analyze the seabed terrain, which is usually presented in the form of a three - dimensional grid or discrete measurement points; Pre - process the terrain data. If the terrain data is: Bd ={(x1, y1, z1),(x1, y1, z1),…,(x m ,y m ,z m )}, where (x j ,y j ,z j ) represents the coordinates of the j - th measurement point, and zj is the seabed depth at this point; then connect every two adjacent data points in the terrain data to obtain a seabed terrain network diagram; then calculate the slope of the seabed terrain network diagram through the established formula: Output the slope S between the jth and the (j + 1)th points j ; z j+1 , z j is the depth of adjacent points, (x j+1 , x j ) and (y j+1 , y j ) are the coordinates of adjacent points;

[0061] Extract several isobaths (sets of isobath points) from the terrain data, select a depth interval, for example, extract an isobath every 1 meter or 2 meters; and in the plane coordinate system (x, y), according to the given depth value, extract all points with the same depth and connect them into an isobath. For each isobath, according to its adjacent depth values and slope changes, it is subdivided into multiple small segments, and each small segment will be used as a path segment for the sand mining equipment; for an isobath with a depth of 5 meters, all points with a depth of 5 meters will be extracted and connected into a closed or open curve to form the basis of the path;

[0062] After the isobaths are extracted, select a suitable path according to the characteristics of the equipment; first calculate the slope: obtain the slope S through the established formula, compare the slope S with the corresponding slope threshold. If the slope S is less than the corresponding threshold, this area is more suitable for the stable operation of the equipment; otherwise, optimize the path and use curve fitting methods to smooth the path (fitting methods include Bezier curves, spline curves, etc., generate smooth curves according to control points to make the path more stable);

[0063] After the path selection and optimization are completed, divide the path into several small segments, and each small segment is a path segment for the equipment to complete a sand mining process; complete each segmented task one by one according to the order of the path;

[0064] During the actual collection process, there is a deviation between the current position and the ideal position of the equipment. Assume that the actual collection point of the sand mining equipment is (x j ', y j ', z j '), and the ideal collection point is (x0, y0, z0), then the accuracy deviation value of the equipment at this position is calculated through the established formula: Output the accuracy deviation value D of the jth point j , and then calculate the average deviation value or the maximum deviation value of the sand mining equipment in the entire area; through the formula: Output the average deviation value Dp, Dmax = max(D1, D2,..., Dm ) Output the maximum deviation value Dmax; then, based on the calculated deviation value Dp or Dmax, divide the precision into different levels. If D ≤ 0.5 meters, it is high precision; if 0.5 < D ≤ 1.0 meters, it is medium precision; if D > 1.0 meters, it is low precision.

[0065] If the device acquisition precision is medium precision or low precision, then analyze whether the precision is related to the environmental quality impact coefficient HZZ and the environmental state impact coefficient E(x, y, z, t); conduct a correlation analysis:

[0066] If there are k calculation samples, and the data includes the precision deviation value D, the environmental quality impact coefficient HZZ, and the environmental state impact coefficient E(x, y, z, t); sort the data by numerical size and assign ranks. If there are equal values, take the average rank; then calculate the difference in ranks of the two variables corresponding to each sample. Then calculate the square d h 1 2 , d h 2 2 , and sum all the d h 1 2 , d h 2 2 to obtain ∑d h 1 2 , ∑d h 2 2 ; then substitute the calculated data into the formula: Output the Spearman rank correlation coefficients r1 and r2. Among them, the Spearman rank correlation coefficient r1 is the correlation coefficient with the environmental quality impact coefficient HZZ, and the Spearman rank correlation coefficient r2 is the correlation coefficient with the environmental state impact coefficient E(x, y, z, t).

[0067] If r1 > 0 or r2 > 0, it is a positive correlation, meaning that when the environmental factors increase, the precision deviation value D increases. If r1 < 0 or r2 < 0, it is a negative correlation, meaning that when the environmental factors increase, the precision deviation value D decreases.

[0068] Correct the precision deviation value D through the correlation between them. Specifically:

[0069] The corrected accuracy deviation value D' is output through the established correction formula: D' = D - β1×HZZ - β2×E(x, y, z, t), where β1 is the correction factor related to r1 and β2 is the correction factor related to r2; the correction factors α1 and β2 are calculated based on the absolute value of the Spearman rank correlation coefficient and actual empirical values, through the established formula: β1 = u1×|r1|, β2 = u2×|r2|, where u1 and u2 are preset weight factors, depending on the influence degree of HZZ and E(x, y, z, t) on D in the actual scenario; |r1| and |r2| are the absolute values of the Spearman rank correlation coefficients; if the corrected accuracy deviation value D', when D' ≤ 0.5 m, no equipment correction is required, if the corrected accuracy deviation value D', when 0.5 < D' ≤ 1.0 m, generate equipment correction instruction one; if the corrected accuracy deviation value D', when D' > 1.0 m, generate equipment correction instruction two

[0070] The execution module is used to obtain the corrected accuracy deviation value D' to generate equipment correction instructions one and two and execute equipment correction;

[0071] When receiving equipment correction instruction one, adjust the sand mining coordinate position of the equipment to the new coordinates and reduce the equipment speed to V1; the new coordinate position is: (x′, y′) = (x + z1, y + z2); V1 = V 原 ×(1 - z3); after performing fine adjustment, monitor the new accuracy deviation value: if D' ≤ 0.5 m, stop correction; if the requirement is still not met, continue to adjust;

[0072] When receiving equipment correction instruction two, through the analysis of the seabed topography data, generate a new sequential acquisition path, and the path coordinate points are (x1′, y1′), (x2′, y2′),...; adjust the sand mining depth, reduce the deviation, and reduce the equipment sand mining speed; after correction, monitor the new accuracy deviation value D'1 in real time, if D'1 ≤ 0.5 m, stop correction, if the requirement is still not met, repeat the large - scale correction process.

[0073] Please refer to Figure 2 As shown, on the other hand, the present invention provides a method for monitoring marine sand mining, including:

[0074] Step one: The monitoring and acquisition module is used to collect the monitoring data during the marine sand mining process, mainly including environmental data, accuracy data, and compliance data. The environmental data includes environmental quality data such as water quality, bottom sediment, and climate, as well as environmental state data such as water flow velocity, temperature, and depth; the accuracy data involves the position, operation parameters, and status of the equipment; the compliance data is used to ensure that the sand mining activities meet the requirements of laws, regulations, and environmental impact assessments.

[0075] Step 2: The environmental monitoring and analysis module analyzes the environmental quality data. First, it obtains the ideal values and current collected values of each environmental factor, calculates the deviation degree of each environmental factor, and performs standardization processing. By assigning weights to each environmental factor, the environmental quality impact coefficient HZZ is calculated and matched with the preset execution range to determine whether the sand mining operation can continue.

[0076] Step 3: When the environmental quality impact coefficient belongs to Execution Range 1, analyze the environmental status data. Calculate through three dynamic factors of water flow velocity, temperature, and depth to quantify their temporal and spatial variations. For example, the water flow velocity calculates displacement through a velocity monitoring device, the temperature calculates the change rate through the heat conduction equation and convection term, and the depth calculates the dynamic water depth through tides and sand mining activities. Finally, integrate each factor and output the environmental status impact coefficient.

[0077] Step 4: The precision monitoring and analysis module analyzes the precision of the sand mining equipment, and obtains the precision deviation value between the actual collection point and the ideal collection point. Further calculate the average deviation value and the maximum deviation value, and evaluate the equipment precision level (high precision, medium precision, or low precision). If the precision is insufficient, perform a correlation analysis to calculate the correlation between the environmental quality impact coefficient and the environmental status impact coefficient and the precision deviation.

[0078] Step 5: The precision monitoring and analysis module analyzes the precision of the sand mining equipment, and obtains the precision deviation value between the actual collection point and the ideal collection point. Further calculate the average deviation value and the maximum deviation value, and evaluate the equipment precision level (high precision, medium precision, or low precision). If the precision is insufficient, perform a correlation analysis to calculate the correlation between the environmental quality impact coefficient and the environmental status impact coefficient and the precision deviation.

[0079] Step 6: The execution module adjusts the equipment according to the correction instructions:

[0080] Equipment correction instruction 1: Adjust the sand mining coordinate position, reduce the equipment speed, and perform fine-tuning until the precision deviation value ≤ 0.5 meters.

[0081] Equipment correction instruction 2: Re-plan the sand mining path, generate a new sequential collection path, adjust the sand mining depth and speed, and significantly correct the equipment operation until the precision deviation value meets the requirements.

[0082] The preferred embodiments of the present invention disclosed above are only used to help illustrate the present invention. The preferred embodiments do not describe all the details in detail, nor do they limit the invention to only the specific implementation manners. Obviously, according to the content of this specification, many modifications and changes can be made. This specification selects and specifically describes these embodiments to better explain the principle and practical application of the present invention, so that those skilled in the relevant technical field can understand and utilize the present invention well. The present invention is only limited by the claims and their full scope and equivalents.

Claims

1. A marine sand mining monitoring system, comprising an environmental monitoring and analysis module and an accuracy monitoring and analysis module, characterized in that: The environmental monitoring and analysis module is used to analyze environmental data, specifically: Analyze the environmental quality data, obtain the ideal value corresponding to each environmental factor under the ideal environmental state of the collection area, collect the current environmental factor value according to the results collected by the monitoring collection module, calculate the deviation degree of the environmental factor, and obtain the deviation degree D of the i-th environmental factor i ; Each deviation value is standardized to a uniform scale by setting up the formula: Output environmental quality impact coefficient HZZ, where ω i is the weight of the i-th factor, D i ' is the standardized deviation value of the i-th environmental factor; Analyze the environmental status data to obtain the environmental status influence coefficient E(x, y, z, t); The accuracy monitoring and analysis module is used to perform sand mining accuracy analysis on the sand mining equipment, specifically: Get the sand mining area, analyze the seabed topography, and pre-process the topographic data to obtain the slope S between the jth and j+1th points j , and then extract several isobaths from the terrain data. After the isobaths are extracted, the appropriate path is selected according to the characteristics of the equipment; first calculate the slope to obtain the slope S; The deviation between the current position of the equipment and the ideal position exists; the actual collection point of the sand mining equipment is (x j ',y j ',z j '), and the ideal acquisition point is (x0, y0, z0), then the accuracy deviation of the device at this position is calculated by the established formula: Output the accuracy deviation value D of the jth point j , and then calculate the average deviation and maximum deviation of sand mining equipment in the entire area; through the formula: Output average deviation value Dp, Dmax = max(D1, D2, ..., D m ) outputs the maximum deviation value Dmax; the correlation between the reanalysis accuracy and the environmental quality influence coefficient HZZ and the environmental state influence coefficient E(x, y, z, t) is used to obtain the Spearman rank correlation coefficients r1 and r2.

2. A marine sand mining monitoring system according to claim 1, characterized in that: It also includes a monitoring acquisition module and an execution module; The monitoring and acquisition module is used to collect monitoring data during the marine sand mining process, and the monitoring data includes environmental data, precision data and compliance data; wherein the environmental data includes environmental quality data and environmental status data, and the environmental quality data includes water quality, bottom quality and climate; the environmental status data includes water flow rate, temperature and depth; the precision data includes location, operation parameters and equipment status data; the compliance data includes operation area, compliance with laws and regulations and environmental impact assessment; The execution module is used to obtain the corrected accuracy deviation value D' to generate device correction instructions 1 and 2 to execute device correction.

3. A marine sand mining monitoring system according to claim 1, characterized in that: The deviation degree D of the i-th environmental factor is obtained i The specific process is: Compare the difference between the current value of each environmental factor and its ideal value to quantify the impact of sand mining on the environment, using the formula: D i =|X i -X iL |Output the deviation degree D of the i-th environmental factor i , X i is the current collected value of the i-th environmental factor, X iL is the ideal value of the i-th environmental factor.

4. A marine sand mining monitoring system according to claim 3, characterized in that: The specific process of obtaining the environmental state influence coefficient E(x, y, z, t) is as follows: Calculate the water velocity factor, collect the water velocity and direction data at different positions (x, y, z), and record the time series. Calculate the displacement of the water flow in space based on the monitored flow velocity V and time interval Δt: S(x, y, z, t) = V(x, y, z, t) × Δt; the cross-sectional area represents the cross-sectional area perpendicular to the water flow direction at a certain spatial position; measure the river depth (z) and width at the specified position (x, y) through the hydrological cross-section instrument; draw the cross-sectional profile, divide the cross-section into small units, and sum them to obtain the cross-sectional area A(x, y, z); through the established formula: Output spatial position (x, y, z) and flow velocity V at time t LS (x,y,z,t), is the partial derivative, which varies with time t and spatial position (x, y, z); Calculate the temperature factor to get the time rate of temperature change The depth factor is calculated to obtain the water depth Ds(x,y,t); through the established formula: Output environmental state influence coefficient E(x,y,z,t), is the convection term of water flow to temperature change, the water depth change ΔDc(x,y,t), and a1, a2, a3 and a4 are all preset weights.

5. A marine sand mining monitoring system according to claim 4, characterized in that: The temperature factor is calculated to obtain the time rate of change of temperature The specific process is: By establishing the formula: Time rate of change of output temperature Among them, α is the preset water body thermal diffusion value, represents the spatial second-order gradient of temperature, is the convection term of water flow on temperature change, and Q1 is the influence of external heat source.

6. A marine sand mining monitoring system according to claim 5, characterized in that: The specific process of calculating the water depth Ds(x, y, t) by the depth factor is as follows: The change of depth factor is caused by tide and sand mining activities, where the tidal change ΔDc(t2) is expressed by a sine function: Output tidal change ΔDc(t2), Ac is the tidal amplitude, θ is the angular frequency of the tide, t is the time variable, φ is the phase shift of the tide; the water depth change ΔDc(x,y,t) caused by human activities is established through the formula: Output the water depth change ΔDc(x,y,t), Vc(x,y,t) is the volume of sand removed by sand mining activities at a certain position (x,y) and time t, Ac(x,y) is the water cross-sectional area corresponding to the sand mining area; through the established formula: Ds(x,y,t)=D0(x,y)+ΔDc(t2)+ΔDc(x,y,t), the water depth Ds(x,y,t) at a certain position (x,y) in the dynamic environment at time t is output, and D0(x,y) is the initial water depth.

7. A marine sand mining monitoring system according to claim 1, characterized in that: The specific process of calculating the slope to obtain the slope S is as follows: The terrain data is: Bd = {(x1, y1, z1), (x1, y1, z1), ..., (x m ,y m ,z m )},(x j ,y j ,z j ) represents the coordinates of the jth measurement point, z j is the seabed depth of the point; connect each two adjacent data points in the topographic data to obtain the seabed topography mesh map; calculate the slope of the seabed topography mesh map, through the established formula: Output the slope S between the jth and j+1th points j ; z j+1 ,z j is the depth of the neighboring point, (x j+1 ,x j ) and (y j+1 ,y j ) are the coordinates of adjacent points; Extract several isobaths from the terrain data, select a depth interval to extract an isobath; and on the plane coordinate system (x, y), extract all points with the same depth according to the given depth value, and connect them into an isobath. For each isobath, it is subdivided into multiple small segments according to its adjacent depth value and slope change. Each small segment will serve as a path segment of the sand mining equipment; after the isobaths are extracted, select a suitable path according to the characteristics of the equipment; calculate the slope: get the slope S through the established formula, compare the slope S with the corresponding slope threshold, if the slope S is less than the corresponding threshold, then the area is more suitable for stable operation of the equipment; otherwise, optimize the path, use the curve fitting method to smooth the path, and divide the path into several small segments.

8. A marine sand mining monitoring system according to claim 7, characterized in that: The specific process of obtaining the Spearman rank correlation coefficients r1 and r2 is: There are k calculation samples, and the data include precision deviation value D, environmental quality impact coefficient HZZ and environmental status impact coefficient E(x, y, z, t); sort the data by numerical value and assign ranks. If equal values ​​appear, take the average rank; calculate the difference between the ranks of the two variables corresponding to each sample Find the square d h 1 2 ,d h 2 2 , all d h 1 2 ,d h 2 2 Add together to get ∑d h 1 2 ,∑d h 2 2 ; Substitute the calculated data into the formula: Output the Spearman rank correlation coefficients r1 and r2; the Spearman rank correlation coefficient r1 is the correlation coefficient with the environmental quality influence coefficient HZZ, and the Spearman rank correlation coefficient r2 is the correlation coefficient with the environmental state influence coefficient E(x, y, z, t); if r1>0 or r2>0, it is a positive correlation, which means that when the environmental factors increase, the precision deviation value D increases; if r1<0 or r2<0, it is a negative correlation, which means that when the environmental factors increase, the precision deviation value D decreases; The precision deviation value D is corrected through the correlation between them: the corrected precision deviation value D' is output through the established correction formula: D'=D-β1×HZZ-β2×E(x,y,z,t), β1 is the correction factor related to r1, β2 is the correction factor related to r2; the correction factors α1 and β2 are obtained through the established formula: β1=u1×|r1|, β2=u2×|r2|, u1 and u2 are preset weight factors; |r1| and |r2| are the absolute values ​​of the Spearman rank correlation coefficient; if the corrected precision deviation value D' is D'≤0.5 meters, no equipment correction is required; if the corrected precision deviation value D' is 0.5<D'≤1.0 meters, equipment correction instruction one is generated; if the corrected precision deviation value D' is D'>1.0 meters, equipment correction instruction two is generated.

9. A method for monitoring marine sand mining, characterized in that: Applied to implement any one of claims 1-8 of the marine sand mining monitoring system, the method comprises: Step 1: The monitoring and acquisition module collects environmental data, accuracy data, and compliance data; Step 2: The environmental monitoring and analysis module calculates the degree of deviation of environmental factors, and calculates the environmental quality impact coefficient through standardization and weight distribution; Step 3: Calculate the dynamic factors of water velocity, temperature and depth, and output the environmental state influence coefficient; Step 4: The accuracy monitoring and analysis module calculates the accuracy deviation value of the equipment, and evaluates the accuracy level of the equipment based on the correlation analysis between the environmental impact coefficient and the accuracy deviation; Step 5: Calculate the correction factor based on the deviation value and correlation analysis, and generate correction instruction 1 and correction instruction 2; Step 6: The execution module adjusts the equipment coordinates, speed, path and working depth according to the correction instructions to ensure that the equipment accuracy meets the requirements.

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