Analysis method and application of seawater flow velocity and wave data

Abstract

The invention provides a seawater flow velocity and wave data analysis method and application, belongs to the technical field of seawater monitoring, and solves the technical problems of low seawater flow velocity and wave data acquisition efficiency, poor analysis accuracy and the like in the prior art. A seawater flow velocity and wave data analysis method and equipment arrangement; collecting data in real time; processing data; extracting data features; comparing and correcting data; establishing a model; statistical analysis; performing visual display; and explaining and reporting a result. The seawater flow velocity and wave data analysis method is applied to the following fields: ocean engineering; ocean resource development; marine environment management; early warning of marine disasters; marine ecology protection; ship traffic management and marine weather forecast; according to the invention, seawater flow velocity and wave data can be collected in real time in different modes; carrying out accurate processing and analysis; multi-party comparison is carried out, errors are removed, and the most accurate data are obtained; establishing a mathematical model, and performing statistical analysis visual display; the reliability is high and the application range is wide.

Description

Technical Field

[0001] The invention belongs to the technical field of seawater monitoring, and relates to a method for analyzing seawater flow velocity and wave data, in particular to an application of the method for analyzing seawater flow velocity and wave data. Background Art

[0002] The ocean is closely related to human life. Frequent global marine environmental problems force humans to pay attention to the ocean and rationally develop marine resources. The ways to study changes in the marine environment are divided into field observations and numerical simulations, and the data from field observations are the basis for numerical simulations. Seawater velocity data is an important parameter for humans to study the process of ocean changes. The flow field distribution of seawater can reflect the characteristics of the topography, weather changes, and water exchange capacity of the sea area to a certain extent. Therefore, accurate seawater velocity data is the basic data for studying changes in the marine environment.

[0003] If long-term continuous high-precision observations are carried out, the amount of data stored in the instrument at the end of the observation is very huge. For example, if the observation is carried out for 25 days and the sampling frequency is 4Hz / s, the length of the data finally obtained will reach more than 8 million. The data occupies a large amount of memory and is more troublesome to use.

[0004] Long-term monitoring of ocean surface currents, understanding and predicting the laws of ocean currents are of great significance to fisheries, shipping, sewage discharge and military affairs.

[0005] The existing analysis methods for seawater velocity and wave data are inefficient and have poor analysis accuracy. They cannot collect seawater velocity and wave data in real time and cannot perform accurate processing and analysis. In addition, they generally only use floating monitoring devices and cannot perform suspended monitoring, make multi-party comparisons, or obtain the most accurate data.

[0006] Based on this, we propose an analysis method for seawater velocity and wave data with high collection efficiency and accurate analysis, which has high reliability and wide application range. Summary of the invention

[0007] The purpose of the present invention is to address the above-mentioned problems in the existing technology and propose an analysis method and application of seawater velocity and wave data. The technical problem to be solved by the invention is: how to achieve high collection efficiency and accurate analysis of seawater velocity and wave data with high reliability and wide application range.

[0008] The purpose of the present invention can be achieved by the following technical solutions:

[0009] A method for analyzing seawater flow velocity and wave data, comprising the following analysis steps:

[0010] Step 1, equipment layout: 1. Set up positioning monitoring devices at fixed monitoring locations at different spatial locations of seawater; 2. Place mobile monitoring devices at different spatial locations of seawater; 3. Data transmission equipment; 4. Other equipment;

[0011] Step 2: Real-time data collection: Real-time seawater velocity and wave data collection is performed through the monitoring device in step 1; accurate position and velocity information can be provided, and wave data includes but is not limited to wave height, period, direction, wind field and temperature;

[0012] Step 3: Data processing: The collected raw data needs to be pre-processed and post-processed. The data processing methods include but are not limited to data cleaning, filtering and denoising. The signal processing and data analysis techniques used include but are not limited to frequency domain analysis and time domain analysis.

[0013] Step 4: Data feature extraction: Extract useful features from the processed data, including but not limited to average flow velocity, maximum wave height, wavelength; used to describe the basic characteristics of seawater flow velocity and waves;

[0014] Step 5: Data comparison and correction: Based on the measured data, multiple comparisons are performed to remove errors, or the average value, the maximum value, or the minimum value is taken to obtain the most accurate data;

[0015] Step 6: Model establishment: Based on the measured data, a mathematical model is established to describe the relationship between the seawater velocity and waves; the model includes but is not limited to a fluid dynamics model and a wave model. By solving these models, the predicted values ​​of the velocity and waves can be obtained;

[0016] Step 7, statistical analysis: Statistical analysis is performed on the measured data and the model prediction values. The statistical quantities include but are not limited to the mean value, variance and correlation coefficient to evaluate the stability and reliability of the data. At the same time, statistical methods are used to analyze the correlation between flow velocity and waves. The statistical characteristics include but are not limited to the probability distribution and spectral characteristics of the average flow velocity and wave height.

[0017] Step 8: Visualization: Visualize the measured data and model predictions in the form of charts, images, and maps to better understand and analyze the data. You can use a variety of visualization tools and techniques, including but not limited to JONSWAP, Matplotlib, Sea-born, and Tableau;

[0018] Step 9: Interpret and report the results: Interpret and summarize the analysis results and write a corresponding report; present the analysis results to relevant personnel in a clear and accurate manner to support decision-making and further research.

[0019] The positioning monitoring device in step 1 includes but is not limited to a wave meter, sonar, radar, GPS, sea surface sensor and seabed pressure sensor.

[0020] The wave meter includes a PUV wave meter, a SUV wave meter and an array wave meter. The PUV wave meter includes but is not limited to Aquadopp, FSI 3D WAVE and MIDAS DWR; the SUV wave meter includes but is not limited to AWAC, and the array wave meter includes but is not limited to ADCP.

[0021] The mobile monitoring device in step 1 includes but is not limited to an acceleration sensor, a GPS wave measuring buoy and a suspended monitoring device.

[0022] The data transmission equipment in step 1 includes but is not limited to satellite sensors;

[0023] The suspension monitoring equipment is arranged in a vertical column distribution, a horizontal plane distribution and a spatial three-dimensional distribution.

[0024] The suspended monitoring device comprises a body, the exterior of which is provided with two symmetrically arranged anti-collision half-covers, the two anti-collision half-covers being mounted in cooperation with each other through a plurality of mounting screws;

[0025] A front cover is provided at the front end of the machine body, a cover head mounting chamber is provided at the front end of the front cover, a rear cover is provided at the rear end of the machine body, an impeller mounting chamber is provided at the rear end of the rear cover, an impeller is rotatably provided at the rear end of the rear cover, the impeller is located inside the impeller mounting chamber, an impeller motor is fixed inside the rear cover, and the output shaft of the impeller motor is drivingly connected to the impeller;

[0026] Waterproof rings are provided between the front cover and the machine body, between the rear cover and the machine body, and between the rear cover and the impeller installation bin. The front side of the machine body is provided with four machine body installation bins evenly distributed around the circumference, and the rear side of the machine body is provided with up-and-down symmetrical machine body installation bins. The rear side of the machine body is provided with left-right symmetrical positioning paddles for rotation. A positioning motor is provided inside the machine body, and the output shaft of the positioning motor is drivingly connected with the positioning paddles.

[0027] The inside of the cover head installation compartment and the body installation compartment are both equipped with cameras, fill lights and sonars. Transparent cover plates are provided at the ends of the cover head installation compartment and the body installation compartment. The transparent cover plates and the cover head installation compartment, as well as the transparent cover plates and the body installation compartment, are installed in coordination through a number of sealing pads and locking screws.

[0028] The body installation compartment and the adjustment paddle extend outwardly from the anti-collision half cover;

[0029] The interior of the machine body is equipped with a working cabin, a built-in water absorption cabin and an air distribution cabin. The working cabin is equipped with a PLC mainboard, a CPS module, a battery, a buzzer and an air compression pump.

[0030] The PLC mainboard is electrically connected to the CPS module, battery, buzzer, air compressor pump, camera, fill light, sonar, impeller motor and positioning motor.

[0031] With the above structure, the anti-collision half cover is used to protect the machine body and has a good anti-collision function. The output shaft of the impeller motor drives the impeller to rotate, providing the moving power of the suspended monitoring equipment. The output shaft of the adjustment motor drives the adjustment paddle to rotate, which is used to adjust the moving direction of the suspended monitoring equipment. The transparent cover plate is convenient for the camera to shoot relevant content. The fill light is used for fill light. The sonar is used to locate the water depth of the suspended monitoring equipment and cooperates with the buzzer to drive away animals. The PLC mainboard controls the timing power-on to save power. The built-in water absorption cabin and the air distribution cabin cooperate with the air compression pump to absorb water and compress air for sinking the suspended monitoring equipment, draining water and decompressing air for floating the suspended monitoring equipment. The waterproof ring is used for sealing and waterproofing. The transparent cover plate and the machine body installation compartment are installed by a number of sealing pads and locking screws to ensure the sealing between the transparent cover plate and the machine body installation compartment.

[0032] The CPS module is used to send out its position information, transmit it to the satellite, and record the position of this suspended monitoring device in real time for recording.

[0033] An application of an analysis method for seawater velocity and wave data, the analysis method for seawater velocity and wave data is applied in the following fields: Marine engineering: used to design and evaluate the stability and safety of marine structures, including but not limited to offshore wind farms and coastal protection projects;

[0034] Marine resource development: used to evaluate the availability and sustainability of marine energy, fishery resources, etc. Wave data can be used to understand the distribution, intensity and periodicity of waves, and then evaluate the resource reserves and development potential of wave energy. At the same time, flow velocity data can be used to evaluate the impact of water flow on wave energy conversion devices to improve wave energy conversion efficiency.

[0035] Marine environmental management: used to monitor and predict environmental problems such as marine pollution and coastal erosion, and to formulate corresponding protection measures;

[0036] Marine disaster warning: used to predict and warn of marine disasters such as tsunamis and storm surges to reduce losses and protect people’s lives and property.

[0037] Marine ecological protection: Wave and current data help scientists understand the dynamic changes of marine ecosystems, assess the impact of human activities on marine ecosystems, and develop corresponding protection measures;

[0038] Vessel traffic management: In vessel traffic management, understanding flow and wave data can help ships plan optimal routes and speeds, and avoid accidents such as collisions or groundings in complex sea conditions. The above data is used to assess the reliability and safety of port facilities.

[0039] Marine weather forecast: Wave and current data are important parameters for marine weather forecast, providing information on sea surface wind fields, tides, and waves, which helps to improve the accuracy and reliability of weather forecasts.

[0040] Compared with the existing technology, the analysis method and application of seawater velocity and wave data have the following advantages:

[0041] Through the cooperation of positioning monitoring devices and mobile monitoring devices, different methods can be used to collect seawater flow rate and wave data in real time;

[0042] The collected raw data needs to be pre-processed and post-processed to ensure the data is authentic and reliable, and the signal processing and data analysis techniques used ensure the accuracy of data analysis;

[0043] Through the combination of data feature extraction and data comparison and correction, feature data can be quickly acquired. Based on the above-mentioned various measured data, multiple comparisons are performed to remove errors and obtain the most accurate data.

[0044] Build a mathematical model and conduct statistical analysis, analyze the correlation between flow velocity and waves, and present it visually. Finally, explain and summarize the analysis results and write a corresponding report.

[0045] The analysis method of seawater velocity and wave data has high reliability and wide application range. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] Figure 1 It is a schematic diagram of the analytical method of the present invention.

[0047] Figure 2 It is a schematic detailed diagram of the analytical method process of the present invention.

[0048] Figure 3 It is a schematic diagram of the measurement method of wave measurement using the SUV method in the present invention.

[0049] Figure 4 It is a schematic diagram of the ADCP wave measurement array calculation method in the present invention.

[0050] Figure 5 It is a comparative schematic diagram of a typical buoy type wave meter in the present invention.

[0051] Figure 6 It is a comparative schematic diagram of a typical buoy type wave meter in the present invention.

[0052] Figure 7 It is a structural schematic diagram of the suspended monitoring device in the present invention.

[0053] Figure 8 It is a schematic diagram of the partially cutaway structure of the suspended monitoring device of the present invention.

[0054] Fig. 9 Schematic diagram of the application of the analytical method of the present invention

[0055] In the figure, 1. front cover body; 2. cover head mounting compartment; 3. transparent cover plate; 4. anti-collision half cover body; 5. machine body mounting compartment; 6. rear cover body; 7. waterproof ring; 8. impeller mounting compartment; 9. impeller; 10. adjustment paddle; 11. mounting screw; 12. machine body; 13. camera; 14. fill light; 15. sonar; 16. sealing gasket; 17. locking screw. DETAILED DESCRIPTION

[0056] The following are specific embodiments of the present invention and the accompanying drawings to further describe the technical solution of the present invention, but the present invention is not limited to these embodiments.

[0057] like Figure 1-Figure 8 As shown, the analysis method of seawater velocity and wave data includes the following analysis steps:

[0058] Step 1, equipment layout: 1. Set up positioning monitoring devices at fixed monitoring locations at different spatial locations of seawater; 2. Place mobile monitoring devices at different spatial locations of seawater; 3. Data transmission equipment; 4. Other equipment;

[0059] Step 2: Real-time data collection: Real-time seawater velocity and wave data collection is performed through the monitoring device in step 1; accurate position and velocity information can be provided, and wave data includes but is not limited to wave height, period, direction, wind field and temperature;

[0060] Step 3: Data processing: The collected raw data needs to be pre-processed and post-processed. The data processing methods include but are not limited to data cleaning, filtering and denoising. The signal processing and data analysis techniques used include but are not limited to frequency domain analysis and time domain analysis.

[0061] Step 4: Data feature extraction: Extract useful features from the processed data, including but not limited to average flow velocity, maximum wave height, wavelength; used to describe the basic characteristics of seawater flow velocity and waves;

[0062] Step 5: Data comparison and correction: Based on the measured data, multiple comparisons are performed to remove errors, or the average value, the maximum value, or the minimum value is taken to obtain the most accurate data;

[0063] Step 6: Model establishment: Based on the measured data, a mathematical model is established to describe the relationship between the seawater velocity and waves; the model includes but is not limited to a fluid dynamics model and a wave model. By solving these models, the predicted values ​​of the velocity and waves can be obtained;

[0064] Step 7, statistical analysis: Statistical analysis is performed on the measured data and the model prediction values. The statistical quantities include but are not limited to the mean value, variance and correlation coefficient to evaluate the stability and reliability of the data. At the same time, statistical methods are used to analyze the correlation between flow velocity and waves. The statistical characteristics include but are not limited to the probability distribution and spectral characteristics of the average flow velocity and wave height.

[0065] Step 8: Visualization: Visualize the measured data and model predictions in the form of charts, images, and maps to better understand and analyze the data. You can use a variety of visualization tools and techniques, including but not limited to JONSWAP, Matplotlib, Sea-born, and Tableau;

[0066] Step 9: Interpret and report the results: Interpret and summarize the analysis results and write a corresponding report; present the analysis results to relevant personnel in a clear and accurate manner to support decision-making and further research.

[0067] The positioning monitoring device in step one includes but is not limited to a wave meter, sonar, radar, GPS, sea surface sensor and seabed pressure sensor.

[0068] Wave meters include PUV wave meters, SUV wave meters and array wave meters. PUV wave meters include but are not limited to Aquadopp, FSI 3D WAVE and MIDASDWR; SUV wave meters include but are not limited to AWAC, and array wave meters include but are not limited to ADCP.

[0069] The mobile monitoring device in step one includes but is not limited to an acceleration sensor, a GPS wave measuring buoy and a suspended monitoring device.

[0070] The data transmission equipment in step 1 includes but is not limited to satellite sensors;

[0071] The arrangement of suspended monitoring equipment is vertical column distribution, horizontal plane distribution and spatial three-dimensional distribution.

[0072] The suspended monitoring device includes a body 12, and two symmetrically arranged anti-collision half-covers 4 are arranged outside the body 12, and the two anti-collision half-covers 4 are installed in cooperation with each other through a plurality of installation screws 11;

[0073] A front cover body 1 is provided at the front end of the machine body 12, a cover head mounting chamber 2 is provided at the front end of the front cover body 1, a rear cover body 6 is provided at the rear end of the machine body 12, an impeller mounting chamber 8 is provided at the rear end of the rear cover body 6, an impeller 9 is rotatably provided at the rear end of the rear cover body 6, the impeller 9 is located inside the impeller mounting chamber 8, an impeller motor is fixed inside the rear cover body 6, and the output shaft of the impeller motor is drivingly connected to the impeller 9;

[0074] A waterproof ring 7 is provided between the front cover body 1 and the machine body 12, between the rear cover body 6 and the machine body 12, and between the rear cover body 6 and the impeller mounting bin 8. The front side of the machine body 12 is provided with four machine body mounting bins 5 evenly distributed around the circumference, the rear side of the machine body 12 is provided with a machine body mounting bin 5 symmetrical up and down, and the rear side of the machine body 12 is rotatably provided with a left-right symmetrical positioning paddle 10, and a positioning motor is provided inside the machine body 12, and the output shaft of the positioning motor is drivingly connected with the positioning paddle 10;

[0075] The inside of the cover head installation chamber 2 and the body installation chamber 5 are both provided with a camera 13, a fill light 14 and a sonar 15, and the ends of the cover head installation chamber 2 and the body installation chamber 5 are provided with a transparent cover plate 3, and the transparent cover plate 3 and the cover head installation chamber 2 and the transparent cover plate 3 and the body installation chamber 5 are installed by a plurality of sealing pads 16 and locking screws 17;

[0076] The body installation compartment 5 and the adjustment paddle 10 extend out of the outside of the anti-collision half cover 4;

[0077] The interior of the machine body 12 is provided with a working cabin, a built-in water absorption cabin and an air distribution cabin, and the interior of the working cabin is provided with a PLC mainboard, a CPS module, a battery, a buzzer and an air compression pump;

[0078] The PLC mainboard is electrically connected to the CPS module, the battery, the buzzer, the air compressor pump, the camera 13, the fill light 14, the sonar 15, the impeller motor and the positioning motor.

[0079] The anti-collision half cover 4 is used to protect the body 12 and has a good anti-collision function. The output shaft of the impeller motor drives the impeller 9 to rotate, providing the moving power of the suspended monitoring equipment. The output shaft of the adjustment motor drives the adjustment paddle 10 to rotate, which is used to adjust the moving direction of the suspended monitoring equipment. The transparent cover plate 3 is convenient for the camera 13 to shoot relevant content. The fill light 14 is used for fill light. The sonar 15 is used to locate the water depth of the suspended monitoring equipment and cooperates with the buzzer to drive away animals. The PLC mainboard controls the timing power-on to save electricity. The built-in water absorption cabin and the air distribution cabin cooperate with the air compression pump to absorb water and compress air for sinking the suspended monitoring equipment, draining water, and decompressing the air for floating the suspended monitoring equipment; the waterproof ring 7 is used for sealing and waterproofing. The transparent cover plate 3 and the body installation compartment 5 are installed by a plurality of sealing pads 16 and locking screws 17 to ensure that the transparent cover plate 3 and the body installation compartment 5 are sealed;

[0080] The CPS module is used to send out its position information, transmit it to the satellite, and record the position of this suspended monitoring device in real time for recording.

[0081] like Fig. 9 As shown, an application of an analysis method for seawater velocity and wave data, the analysis method for seawater velocity and wave data is applied in the following fields: Marine engineering: used to design and evaluate the stability and safety of marine structures, including but not limited to offshore wind farms and coastal protection projects;

[0082] Marine resource development: used to evaluate the availability and sustainability of marine energy, fishery resources, etc. Wave data can be used to understand the distribution, intensity and periodicity of waves, and then evaluate the resource reserves and development potential of wave energy; at the same time, flow velocity data can be used to evaluate the impact of water flow on wave energy conversion devices to improve wave energy conversion efficiency

[0083] Marine environmental management: used to monitor and predict environmental problems such as marine pollution and coastal erosion, and to formulate corresponding protection measures;

[0084] Marine disaster warning: used to predict and warn marine disasters such as tsunamis and storm surges to reduce losses and protect people’s lives and property;

[0085] Marine ecological protection: Wave and current data help scientists understand the dynamic changes of marine ecosystems, assess the impact of human activities on marine ecosystems, and develop corresponding protection measures;

[0086] Vessel traffic management: In vessel traffic management, understanding flow and wave data can help ships plan optimal routes and speeds, and avoid accidents such as collisions or groundings in complex sea conditions. The above data is used to assess the reliability and safety of port facilities.

[0087] Marine weather forecast: Wave and current data are important parameters for marine weather forecast, providing information on sea surface wind fields, tides, and waves, which helps to improve the accuracy and reliability of weather forecasts.

[0088] Working principle of the present invention:

[0089] Step 1, equipment layout: 1. Set up positioning monitoring devices at fixed monitoring positions at different spatial positions of seawater. The positioning monitoring devices include wave meters, sonar, radar, GPS, sea surface sensors, seabed pressure sensors and other components. The wave meters are PUV wave meters, SUV wave meters and array wave meters. The PUV wave meters are Aquadopp, FSI 3DWAVE and MIDASDWR; the SUV wave meter is AWAC, and the array wave meter is ADCP; 2. Place mobile monitoring devices at different spatial positions of seawater, including acceleration sensors, GPS wave measuring buoys and suspended monitoring equipment; 3. Data transmission equipment includes satellite sensors and other equipment; 4. Other equipment;

[0090] Step 2: Real-time data collection: The seawater velocity and wave data at the fixed position are collected in real time by the positioning monitoring device in step 1; a number of mobile monitoring devices are distributed vertically, horizontally and in space according to needs, and the mobile monitoring devices collect real-time seawater velocity and wave data as the seawater flows; accurate position and speed information can be provided, and the wave data includes wave height, period, direction, wind field and temperature;

[0091] The anti-collision half cover 4 is used to protect the body 12 and has a good anti-collision function. The output shaft of the impeller motor drives the impeller 9 to rotate, providing the moving power of the suspended monitoring equipment. The output shaft of the adjustment motor drives the adjustment paddle 10 to rotate, which is used to adjust the moving direction of the suspended monitoring equipment. The transparent cover plate 3 is convenient for the camera 13 to shoot relevant content. The fill light 14 is used for fill light. The sonar 15 is used to locate the water depth of the suspended monitoring equipment and cooperates with the buzzer to drive away animals. The PLC mainboard controls the timing power-on to save electricity. The built-in water absorption cabin and the air distribution cabin cooperate with the air compression pump to absorb water and compress air for sinking the suspended monitoring equipment, draining water, and decompressing the air for floating the suspended monitoring equipment; the waterproof ring 7 is used for sealing and waterproofing. The transparent cover plate 3 and the body installation compartment 5 are installed by a plurality of sealing pads 16 and locking screws 17 to ensure that the transparent cover plate 3 and the body installation compartment 5 are sealed;

[0092] The CPS module is used to send out its position information, transmit it to the satellite, and record the position of this suspended monitoring device in real time for recording.

[0093] The seabed pressure sensor measures the pressure changes caused by the fluctuation of waves. The measured wave period is shorter and more accurate. The theoretical formula for the change of dynamic pressure at the seabed pressure sensor under the water surface with time t derived from the linear wave theory is P(t) = ρ ωgAcoshk(d+z) / coshkdcos(kx-ωt); where: P is pressure; d is water depth; g is gravitational acceleration; z axis is positive; k is wave number; ω is wave circular frequency; A is free surface wave amplitude; ρ ω is the density of water.

[0094] PUV method of wave meter: In the PUV measurement method, in addition to using the traditional pressure measurement method to statistically calculate the non-directional wave elements, the wave meter uses the acoustic Doppler principle to calculate the flow velocities (u and v) in the horizontal and vertical directions to obtain the flow direction; there are many wave meters that use the PUV method to calculate waves, the main representatives are Aquadopp (1M), FSI 3D WAVE, MIDASDWR, etc.

[0095] Wave meter SUV method: In the SUV measurement method, in addition to using the acoustic Doppler principle to calculate the flow velocity (u and v) in the horizontal and vertical directions to obtain the flow direction, the wave meter uses the acoustic wavefront tracking method to perform wave height and wave breaking spectrum statistics; SUV is different from PUV in that the measurement of the wave surface is changed to acoustic measurement instead of pressure sensor measurement; the main representative equipment for calculating waves using the SUV method is AWAC.

[0096] Array method of wave meter: The wave meter uses the flow velocity of three layers of units in 3 to 4 beam directions close to the water surface as an array, and inverts the orbital flow velocity of these units to obtain elements such as wave height and wave direction. The array method generally uses MLM (maximum likelihood statistical method) to perform statistics on wave direction, etc. during the processing process; the main representative equipment for calculating waves using the array method is ADCP.

[0097] There are two major categories of wave measuring buoys. One is the acceleration sensor, which uses the double integral of the acceleration measured by the high-precision acceleration sensor to calculate the wave height and wave spectrum series. The other is the GPS wave measuring buoy, which calculates the wave parameters by detecting the relative movement speed of the GPS. The buoy used for wave measurement calculates the wave direction through a compass or motion sensor.

[0098] Remote wave measurement, remote wave measurement refers to a measurement method that is different from direct contact with seawater. It is generally completed by illuminating the sea surface waves and receiving reflections using high-frequency or ultra-high-frequency radar waves.

[0099] Step 3: Data processing: The collected raw data needs to be pre-processed and post-processed. The data processing methods include but are not limited to data cleaning, filtering and denoising. The signal processing and data analysis techniques used include but are not limited to frequency domain analysis and time domain analysis.

[0100] The filtering method is proposed from engineering technology. It is the specific application and development of linear theory. From the perspective of system response analysis, the filter is actually a system. The filtered function x(t) can be regarded as the input of the system, and the filtered result y(t) can be regarded as the output of the system. The linear filtering process can be expressed by formula (1):

[0101]

[0102] In the filtering method, the impulse response function h(τ) is called the time function, weight function or filter factor of the filter. Common filters generally have time-invariant characteristics, which correspond to time-invariant constant coefficient linear systems. That is to say, for this kind of filter, when the input is x(t) and the output is y(t), then for any t1, when the input is x(t+t1), the output must be y(t+t1). This shows that the physical characteristics of the filter are invariant to time, that is, when the input signal is delayed by t1, the waveform of the output signal does not change, but the output signal is also delayed by t1.

[0103] In the filtering method, the Fourier transform H(f) of h(τ) in equation (1) is called the spectral function of the filter.

[0104] Let F x and F y are the Fourier transforms of x(t) and the filtering result y(t), respectively. From (1), we can get: y (f)=H(f)Fx(f) (2)

[0105] The frequency response function, that is, the spectral function H(f) of the filter here, can be written as Where H(f) represents the amplitude ratio of output to input, Indicates the phase difference between the output and the input. In this way, as long as H(f) is properly selected, the filtering requirements can be met. For example, sometimes the relationship between the above-mentioned observation data, namely the effective signal and the noise signal, can be written as follows:

[0106] x(t)=s(t)+n(t)(3)

[0107] And s(t) contains only low-frequency signals, n(t) contains only high-frequency signals, and their frequency spectrum F s (f) and F n (f) has different frequency domain distribution characteristics. When |f|>f a , F s (f) = 0; and F s (f) = F n (f), when |f|≤f a , F s (f) = 0; and F X (f) = Fs (f). In this way, a filter can be designed so that its spectral function has the following properties:

[0108]

[0109] From equation (3) and the fact that Fourier transform is a linear transform, we know that the spectrum of the signal before filtering is F X (f) = F s (f)+F n (f)(5)

[0110] Assume that the result of filtering is y(t), and its spectrum F y (f) is F y (f)=H(f)F X (f) (6)

[0111] From equations (4), (5) and (6), we can get

[0112]

[0113] F y (f) Perform inverse Fourier transform to obtain the effective signal s(t). Therefore, after filtering, high-frequency noise is eliminated and low-frequency effective signals are retained, thus achieving the purpose of filtering.

[0114] Step 4: Data feature extraction: Extract useful features from the processed data, including but not limited to average flow velocity, maximum wave height, wavelength; used to describe the basic characteristics of seawater flow velocity and waves;

[0115] Step 5: Data comparison and correction: Based on the above-mentioned measured data, multiple comparisons are performed to remove errors, or the average value, the maximum value, or the minimum value is taken to obtain the most accurate data;

[0116] Step 6: Model establishment: Based on the measured data, a mathematical model is established to describe the relationship between the seawater velocity and waves; the model includes but is not limited to a fluid dynamics model and a wave model. By solving these models, the predicted values ​​of the velocity and waves can be obtained;

[0117] Step 7, statistical analysis: Statistical analysis is performed on the measured data and the model prediction values. The statistical quantities include but are not limited to the mean value, variance and correlation coefficient to evaluate the stability and reliability of the data. At the same time, statistical methods are used to analyze the correlation between flow velocity and waves. The statistical characteristics include but are not limited to the probability distribution and spectral characteristics of the average flow velocity and wave height.

[0118] Step 8: Visualization: Visualize the measured data and model predictions in the form of charts, images, and maps to better understand and analyze the data. Various visualization tools and techniques can be used, including but not limited to JONSWAP, Matplotlib, Sea-born, and Tableau.

[0119] Step 9: Interpret and report the results: Interpret and summarize the analysis results and write a corresponding report; present the analysis results to relevant personnel in a clear and accurate manner to support decision-making and further research.

[0120] In summary, by cooperating with the positioning monitoring device and the mobile monitoring device, different methods can be used to collect seawater velocity and wave data in real time;

[0121] The collected raw data needs to be pre-processed and post-processed to ensure the data is authentic and reliable, and the signal processing and data analysis techniques used ensure the accuracy of data analysis;

[0122] Through the combination of data feature extraction and data comparison and correction, feature data can be quickly acquired. Based on the above-mentioned various measured data, multiple comparisons are performed to remove errors and obtain the most accurate data.

[0123] Build a mathematical model and conduct statistical analysis, analyze the correlation between flow velocity and waves, and present it visually. Finally, explain and summarize the analysis results and write a corresponding report.

[0124] The analysis method of seawater velocity and wave data has high reliability and wide application range.

[0125] The specific embodiments described herein are merely examples of the spirit of the present invention. Those skilled in the art may make various modifications or additions to the specific embodiments described or replace them in similar ways, but they will not deviate from the spirit of the present invention or exceed the scope defined by the appended claims.

Claims

1. A method for analyzing seawater velocity and wave data, characterized in that: The analysis steps include: Step 1, equipment layout:

1. Set up positioning monitoring devices at fixed monitoring locations at different spatial locations of seawater; 2. Place mobile monitoring devices at different spatial locations of seawater; 3. Data transmission equipment; 4. Other equipment; Step 2: Real-time data collection: Real-time seawater velocity and wave data collection is performed through the monitoring device in step 1; accurate position and velocity information can be provided, and wave data includes but is not limited to wave height, period, direction, wind field and temperature; Step 3: Data processing: The collected raw data needs to be pre-processed and post-processed. The data processing methods include but are not limited to data cleaning, filtering and denoising. The signal processing and data analysis techniques used include but are not limited to frequency domain analysis and time domain analysis. Step 4: Data feature extraction: Extract useful features from the processed data, including but not limited to average flow velocity, maximum wave height, wavelength; used to describe the basic characteristics of seawater flow velocity and waves; Step 5: Data comparison and correction: Based on the measured data, multiple comparisons are performed to remove errors, or the average value, the maximum value, or the minimum value is taken to obtain the most accurate data; Step 6: Model establishment: Based on the measured data, a mathematical model is established to describe the relationship between the seawater velocity and waves; the model includes but is not limited to a fluid dynamics model and a wave model. By solving these models, the predicted values ​​of the velocity and waves can be obtained; Step 7, statistical analysis: Statistical analysis is performed on the measured data and the model prediction values. The statistical quantities analyzed include but are not limited to the mean value, variance and correlation coefficient to evaluate the stability and reliability of the data. At the same time, statistical methods are used to analyze the correlation between flow velocity and waves. Statistical characteristics include, but are not limited to, average flow velocity, probability distribution of wave height, and spectral characteristics; Step 8: Visualization: Visualize the measured data and model prediction values ​​in the form of charts, images and maps to better understand and analyze the data; A variety of visualization tools and techniques can be used including but not limited to JONSWAP, Matplotlib, Sea-born, and Tableau; Step 9: Interpret and report the results: Interpret and summarize the analysis results and write a corresponding report; present the analysis results to relevant personnel in a clear and accurate manner to support decision-making and further research.

2. The method for analyzing seawater velocity and wave data according to claim 1, characterized in that: The positioning monitoring device in step 1 includes but is not limited to a wave meter, sonar, radar, GPS, sea surface sensor and seabed pressure sensor.

3. The method for analyzing seawater velocity and wave data according to claim 2, characterized in that: The wave meter includes a PUV wave meter, a SUV wave meter and an array wave meter. The PUV wave meter includes but is not limited to Aquadopp, FSI 3DWAVE and MIDASDWR; the SUV wave meter includes but is not limited to AWAC, and the array wave meter includes but is not limited to ADCP.

4. The method for analyzing seawater velocity and wave data according to claim 3, characterized in that: The mobile monitoring device in step 1 includes but is not limited to an acceleration sensor, a GPS wave measuring buoy and a suspended monitoring device.

5. The method for analyzing seawater velocity and wave data according to claim 4, characterized in that: The data transmission equipment in step 1 includes but is not limited to satellite sensors.

6. The method for analyzing seawater velocity and wave data according to claim 5, characterized in that: The suspension monitoring equipment is arranged in a vertical column distribution, a horizontal plane distribution and a spatial three-dimensional distribution.

7. The method for analyzing seawater velocity and wave data according to claim 6, characterized in that: The suspended monitoring device comprises a machine body (12), the exterior of the machine body (12) is provided with two symmetrically arranged anti-collision half-cover bodies (4), the two anti-collision half-cover bodies (4) are mounted in cooperation with each other via a plurality of mounting screws (11); a front cover body (1) is provided at the front end of the machine body (12), a cover head mounting chamber (2) is provided at the front end of the front cover body (1), a rear cover body (6) is provided at the rear end of the machine body (12), an impeller mounting chamber (8) is provided at the rear end of the rear cover body (6), an impeller (9) is rotatably provided at the rear end of the rear cover body (6), and the impeller (9) is rotatably mounted at the rear end of the rear cover body (6). ) is located inside the impeller installation bin (8), an impeller motor is fixed inside the rear cover body (6), and the output shaft of the impeller motor is drivingly connected to the impeller (9); a waterproof ring (7) is provided between the front cover body (1) and the machine body (12), between the rear cover body (6) and the machine body (12), and between the rear cover body (6) and the impeller installation bin (8); four machine body installation bins (5) are evenly distributed on the front side of the machine body (12), and the machine body installation bins (5) are symmetrical up and down on the rear side of the machine body (12); the rear side of the machine body (12) is provided with a waterproof ring (7) between the front cover body (1) and the machine body (12), and ... waterproof ring (7) is provided between the front cover body (1) and the machine body (12), and the waterproof ring (7) is provided between the front cover body (1) and the impeller installation bin (8), and the waterproof ring (7) is provided between the front cover body (1) and the machine body (12), and the waterproof ring (7) is provided between the front cover body (1) and the impeller installation bin (8), and the waterproof ring (7) is provided between the front cover body (1) and the impeller installation bin (8), and the waterproof ring The machine body (12) is provided with a left-right symmetrical position adjustment paddle (10), a position adjustment motor is provided inside the machine body (12), and the output shaft of the position adjustment motor is drivingly connected to the position adjustment paddle (10); a camera (13), a fill light (14) and a sonar (15) are provided inside the cover head installation chamber (2) and the machine body installation chamber (5), and a transparent cover plate (3) is provided at the end of the cover head installation chamber (2) and the machine body installation chamber (5), and a plurality of holes are provided between the transparent cover plate (3) and the cover head installation chamber (2) and between the transparent cover plate (3) and the machine body installation chamber (5). The sealing pad (16) and the locking screw (17) are installed in coordination; the machine body installation compartment (5) and the position adjustment paddle (10) extend out of the outer side of the anti-collision half cover (4); a working cabin, a built-in water absorption cabin and an air distribution cabin are arranged inside the machine body (12); a PLC mainboard, a CPS module, a storage battery, a buzzer and an air compression pump are arranged inside the working cabin; the PLC mainboard is electrically connected to the CPS module, the storage battery, the buzzer, the air compression pump, the camera (13), the fill light (14), the sonar (15) as well as the impeller motor and the position adjustment motor.

8. Application of the method for analyzing seawater velocity and wave data according to claims 1-7, characterized in that: The analysis method of seawater velocity and wave data is applied in the following fields: Marine engineering: used to design and evaluate the stability and safety of marine structures, including but not limited to offshore wind farms and coastal protection projects; Marine resource development: used to evaluate the availability and sustainability of marine energy, fishery resources, etc. Wave data can be used to understand the distribution, intensity and periodicity of waves, and then evaluate the resource reserves and development potential of wave energy; at the same time, flow velocity data can be used to evaluate the impact of water flow on wave energy conversion devices to improve wave energy conversion efficiency Marine environmental management: used to monitor and predict environmental problems such as marine pollution and coastal erosion, and to formulate corresponding protection measures; Marine disaster warning: used to predict and warn marine disasters such as tsunamis and storm surges to reduce losses and protect people’s lives and property; Marine ecological protection: Wave and current data help scientists understand the dynamic changes of marine ecosystems, assess the impact of human activities on marine ecosystems, and develop corresponding protection measures; Vessel traffic management: In vessel traffic management, understanding flow and wave data can help ships plan optimal routes and speeds, and avoid accidents such as collisions or groundings in complex sea conditions. The above data is used to assess the reliability and safety of port facilities. Marine weather forecast: Wave and current data are important parameters for marine weather forecast, providing information on sea surface wind fields, tides, and waves, which helps to improve the accuracy and reliability of weather forecasts.

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