CN112665557A - Wave data processing method and device, electronic equipment and scale storage medium - Google Patents
Wave data processing method and device, electronic equipment and scale storage medium Download PDFInfo
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Abstract
The scheme discloses a wave data processing method, which comprises the following steps: carrying out frequency domain integration processing on the resultant acceleration data of the triaxial acceleration of the waves to obtain integration result data; and carrying out data fusion on the integration result data, the resultant acceleration data and the air pressure data to obtain wave height information. According to the scheme, the acceleration data of the waves are subjected to integral processing through a frequency domain integral method to obtain frequency domain integral result data, so that an accumulated error generated when integral calculation displacement is caused by sampling noise is avoided, meanwhile, data fusion is carried out on the frequency domain integral result data, the resultant acceleration data and the air pressure data, the frequency domain integral result data are corrected, and accurate wave height information is obtained.
Description
Technical Field
The invention relates to the field of marine data monitoring. And more particularly, to a wave data processing method, apparatus, electronic device, and scale storage medium.
Background
The ocean has abundant resources, and people are constantly attracted to explore and develop the ocean. However, marine disasters caused by natural disasters such as typhoons and earthquakes have a serious influence on coastal areas. Therefore, monitoring of ocean conditions is urgently needed to reduce disaster loss and improve economic benefits.
Among the various ocean data indices, wave data is particularly important. Generally, for wave data monitoring, the following three methods are adopted:
1. the large wave meter for shore is adopted to carry out visual observation on the shore, and although the approximate wave height can be obtained by the method, the observation on the wave period is not accurate and is not suitable for observation at night and in severe weather.
2. Wave measuring rod type, pressure type, acoustic type, gravity type, remote sensing wave measuring and the like.
3. With the development of science and technology, remote sensing technology and gravity type are more and more common, wherein the gravity type is most widely applied due to the advantages of low cost, high precision and good real-time property. The gravity type principle is that the height and the period of waves are calculated through the change of the gravity acceleration of a wave buoy when waves float up and down along with sea waves, wherein the gravity acceleration needs to be acquired by an acceleration sensor.
At present, the common wave measuring device based on gravity acceleration comprises an SZF type wave buoy, an OSB-W4 type wave buoy and the like. The buoys obtain the wave height by performing time domain second integration on the acceleration, and due to the performance limitation of the sensor, the acquired acceleration data often have high-frequency harmonic waves, and the direct integration can cause a result to generate a large accumulative error, so that the reliability of the observation data is reduced. In addition, these wave buoys generally determine the wave direction directly through an electronic compass, with relatively low accuracy.
Disclosure of Invention
The scheme aims to provide a wave data processing method and device, electronic equipment and a scale storage medium.
In order to achieve the purpose, the technical scheme is as follows:
in a first aspect, the present disclosure provides a wave data processing method, which performs integration processing on combined acceleration data of triaxial accelerations of a wave by using a frequency domain integration method to obtain integration result data, so as to avoid an accumulated error generated when an integral computation displacement is caused by sampling noise. However, the frequency domain integration method may cause a loss of power spectrum by filtering out the spectrum in the non-frequency band, i.e. may generate an eye diagram effect. Therefore, the frequency domain integration result data, the resultant acceleration data and the air pressure data are further subjected to data fusion, the frequency domain integration result data are corrected, and accurate wave height information is obtained.
In a second aspect, the present solution provides a wave data processing apparatus, the apparatus comprising:
the integration module is used for carrying out frequency domain integration processing on the combined acceleration data of the triaxial acceleration of the waves to obtain integration result data;
and the fusion module is used for carrying out data fusion on the integral result data, the resultant acceleration data and the air pressure data to obtain wave height information.
In a third aspect, the present solution provides an apparatus comprising: a memory, one or more processors; the memory is connected with the processor through a communication bus; the processor is configured to execute instructions in the memory; the storage medium has stored therein instructions for carrying out the various steps of the wave data processing method as described above.
In a fourth aspect, the present solution provides a computer-readable storage medium, on which a computer program is stored, which program, when being executed by a processor, realizes the steps of the wave data processing method as described above.
The invention has the following beneficial effects:
according to the scheme, the acceleration data of the waves are subjected to integral processing through a frequency domain integral method to obtain frequency domain integral result data, so that an accumulated error generated when integral calculation displacement is caused by sampling noise is avoided, meanwhile, data fusion is carried out on the frequency domain integral result data, the resultant acceleration data and the air pressure data, the frequency domain integral result data are corrected, and accurate wave height information is obtained;
according to the scheme, the wave period information can be accurately determined through the wave height information;
according to the scheme, the wave direction identification method based on linear fitting and plane segmentation is adopted, and the absolute wave direction is calculated according to wave height zero-crossing data, vertical direction acceleration data and three-axis magnetic field data, so that the accuracy of wave direction information is improved.
Drawings
In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings needed to be used in the description of the embodiments will be briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without creative efforts.
Fig. 1 shows a schematic diagram of the wave data processing method according to the present solution;
FIG. 2 is a schematic diagram of the step of obtaining integration result data according to the present scheme;
FIG. 3 is a schematic diagram of the step of obtaining wave height information according to the present solution;
fig. 4 shows a schematic diagram of the step of determining wave period information according to the present solution;
fig. 5 shows a schematic diagram of the step of determining wave direction information according to the present solution;
figure 6 shows a schematic view of a wave data processing device according to the solution;
fig. 7 shows a schematic view of an electronic device according to the present solution;
FIG. 8 is a schematic diagram illustrating the conversion of time domain acceleration data into frequency domain data according to the present disclosure;
FIG. 9 is a diagram illustrating an eye diagram effect generated by frequency domain integrated data in the present scheme;
FIG. 10 is a schematic diagram showing a wave height curve obtained by fusing acceleration data, frequency domain integration result data and air pressure data in the present scheme;
fig. 11 shows a schematic diagram of calculating an absolute wave direction by wave height information, an X-axis/Y-axis acceleration trajectory and a Z-axis euler angle in the present scheme.
Detailed Description
In order to make the technical solutions and advantages of the present invention more apparent, embodiments of the present invention will be described in detail with reference to the accompanying drawings. It is clear that the described embodiments are only a part of the embodiments of the present application, and not an exhaustive list of all embodiments. It should be noted that the embodiments and features of the embodiments in the present application may be combined with each other without conflict.
Through analysis and research of the prior art, in the statistical process of wave information such as wave period, wave height, wave direction and the like, the wave information processing speed is too low due to factors such as an acquisition device, a processing mode and the like, and even the accuracy of the wave information is influenced;
in addition, when the frequency domain integration processing is performed on the wave acceleration data, the loss of the power spectrum is caused by filtering out the frequency spectrum in the non-frequency band, namely, the eye diagram effect is generated, so that the accuracy of the data is influenced.
Therefore, the scheme aims to provide a wave data processing method, a wave data processing device, electronic equipment and a scale storage medium, which can eliminate the accumulated error generated by calculating displacement and correct the frequency domain integration result so as to obtain accurate wave height information and calculate wave period information and wave direction information on the basis of the wave height information and the frequency domain integration result.
Hereinafter, a wave data processing method proposed by the present scheme will be described in detail with reference to the accompanying drawings. As shown in fig. 1, the method may include the steps of:
step S1, carrying out frequency domain integration processing on the resultant acceleration data of the triaxial acceleration of the waves to obtain integration result data;
and step S2, carrying out data fusion on the integration result data, the resultant acceleration data and the air pressure data to obtain wave height information.
The triaxial wave acceleration data used in step S1 of the present embodiment may be acquired by a buoy device equipped with a ten-axis sensor, the triaxial acceleration, the triaxial magnetic field, the euler angle, and the air pressure information of the wave. The acceleration of the X axis, the acceleration of the Y axis and the acceleration of the Z axis are collected through a three-axis accelerometer in a ten-axis sensor. When the ten-axis sensor carries out acceleration acquisition, displacement integral accumulated errors can be caused due to acceleration linear deviation, and magnetic field linear deviation can occur at the same time, so that in order to reduce the accumulated errors and the linear deviation of a magnetic field, the linear correction can be carried out on acceleration and magnetic field data by adopting a least square method so as to ensure that the acceleration data is symmetrical about a zero point, and when the sensor is horizontally placed, the average value of the acceleration of an X axis and a Y axis is 0, the average value of the acceleration of a Z axis is 1 (the unit is g), and meanwhile, the central point of the magnetic field can be ensured to be positioned at the origin of coordinates of the ten-axis. When the static ten-axis sensor is required to be in different poses after least square normal linear correction, the resultant vector coordinate point cloud obtained by the three-axis accelerometer and the resultant vector coordinate point cloud obtained by calculation of the three-axis magnetic field can fall on a spherical surface with (0,0) as the origin of coordinates, wherein the spherical radius formed by the point cloud of the acceleration resultant vector is 1, and the spherical radius multiplied by the point cloud of the magnetic field resultant vector is required to be the intensity of the geomagnetic field of the sea area where the wave buoy is located.
In the scheme, in order to avoid the problem of accumulated errors generated during integral calculation displacement caused by acceleration sampling noise, frequency domain integral processing can be respectively carried out on triaxial acceleration data of waves. Specifically, the method comprises the following steps: the Z-axis acceleration data of the sensor can be converted into a frequency domain by Fast Fourier Transform (FFT), and a frequency spectrum which is about 1mHz and consists of 2048 points can be obtained. And integrating the Z-axis acceleration in a frequency domain, namely calculating positive and negative discrete circle frequency vectors, then taking the square of each dimension value, dividing the frequency components by the corresponding circle frequency vectors respectively, and then taking the inverse (namely, the complex numbers rotate 180 degrees clockwise) to obtain the Z-axis displacement after the Z-axis acceleration value frequency domain secondary integration. Considering that the wave period is generally between 2s and 20s, i.e. the wave frequency is between 0.5Hz and 0.05Hz, the effective band in the frequency spectrum can be considered to be between the 51 st to 512 th frequency components and the 1536 th to 1996 th frequency components in the frequency spectrum, and since the frequency spectrum is symmetrical, the frequency spectrum outside the wave frequency spectrum is filtered, i.e. the frequency components in the range of 1 to 51 frequency components, 513 to 1536 frequency components, 1997 to 2048 frequency components are zeroed out. And returning the frequency domain displacement to the time domain through inverse Fourier transform (IFFT) to obtain time domain displacement, namely the vertical displacement of the beacon fluctuating along with the waves, wherein the average value of the displacement is 0 because the accumulated error component is removed in the previous step. Here, the acceleration frequency domain processing will be described by taking a process of performing frequency domain integration processing on the Z-axis acceleration as an example. The frequency domain integration processing modes of the X axis and the Y axis are basically the same, and are not described herein again.
In step S1, in order to avoid the problem of accumulated error in integral computation of displacement due to acceleration sampling noise, the processing speed of the wave acceleration is increased, and the frequency domain integration processing may be directly performed on the resultant acceleration data of the triaxial acceleration of the wave. In addition, according to the characteristics of the waves, the buoy device for collecting wave acceleration data reciprocates along with the waves, and the average displacement is 0, so that the method is more suitable for integrating the acceleration by a frequency domain integration method. Specifically, the obtained three-axis acceleration within a certain period of time is obtained, and the resultant acceleration of the three-axis acceleration is calculated and sequentially used as a time domain data set. And carrying out fast Fourier transform on the time domain data set to obtain a frequency domain data set. And then, sequentially carrying out frequency domain integration, integration phase transformation and integration frequency domain transformation on the frequency domain data set to obtain an integrated frequency domain data set. And further, performing frequency domain filtering processing on the integrated frequency domain data set by using frequency domain rectangular window filtering to obtain a filtered frequency domain data set. And finally, performing inverse Fourier transform processing on the filtered frequency domain data group, and returning the frequency domain data to the time domain, thereby obtaining integral result data. In one embodiment, a frequency domain integral calculation may be performed every 2048 sets of acceleration data (about 17 minutes) to obtain a displacement curve of the wave buoy during the time period.
When the frequency domain integration processing is carried out on the wave acceleration data, the loss of a power spectrum is caused by filtering out a non-frequency-band frequency spectrum, and then an eye pattern effect is generated; in addition, the time domain integral wave height has a large accumulated error, the air pressure value conversion height changes slowly, and temperature drift exists in long-term work, so that the accuracy of the wave height information is seriously influenced. Therefore, in step S2, the integration result data, the resultant acceleration data, and the air pressure data are subjected to data fusion, and the frequency domain integration result data are corrected; and the data fusion mode is used for mutually making up for the shortages, so that more accurate wave height information can be obtained. Specifically, the manner of obtaining the wave height may include the following three types: 1. the displacement after the acceleration is integrated in the time domain is used as the height information of the wave; 2. the displacement of the acceleration frequency domain integral is taken as the height information of the waves; 3. wave height information obtained by linear calculation of air pressure values. Wherein, because the displacement is the quadratic integral of the acceleration, the displacement after the acceleration is integrated in the time domain should be similar to the displacement shape of the frequency domain integration. At low altitude, the altitude displacement is inversely related to the barometric pressure value, and the barometric pressure value of the barometer can be linearly calculated to obtain altitude change information. Therefore, the three types of data can be mutually made up for each other in a data fusion mode, and more accurate wave height information can be obtained.
In one embodiment, the wave height is calculated from a time domain perspective, resulting in the following state transition equation:
real-time height, speed and acceleration information can be obtained through a state transition equation.
Where k is a discretized variable of the continuous time T and represents a sampling time within a data processing cycle, k +1 represents the next sampling time, and T represents the next sampling timesIndicating that the sampling frequency is according to the state transition equation. The data that can thus be observed directly or indirectly are acceleration values
(including gravitational acceleration), barometric pressure P, and frequency domain integral value
According to the air pressure-height formula, an observation equation can be obtained:
and substituting the state transition matrix and the observation equation into a Kalman data fusion equation, sequentially calculating the state prediction (height, speed and acceleration), calculating the optimal estimation of the state by the covariance prediction and the gain matrix, and taking the height value in the optimal estimation as the final data fusion result, namely the final wave height information.
In order to enable the fused data to be more accurate, after the Kalman data fusion, the covariance matrix of the Kalman data fusion can be updated, and the updated covariance matrix can be used for the next Kalman data fusion calculation.
In step S3, the period information of the wave may be further determined according to the wave height information. Specifically, the upper zero crossing point information of the wave can be determined according to a data set of wave displacement information obtained through frequency domain integration; then according to a predetermined constraint condition, screening the upper span zero point position which accords with the constraint condition; taking the upper span zero point position as a dividing point, and extracting a single wave; traversing each wave, and determining the peak-valley value of each wave; and determining the period information of the waves according to the height information and the peak-valley value of each wave. In one embodiment, the maximum wave height H may be passedmax Front 1/10 wave height
Front 1/3 wave height
And average wave height HavgAnd calculating the period of the wave. For calculating the four kinds of wave height information, 2048 points of displacement information obtained through frequency domain integration can be divided into a plurality of waves according to zero crossing point information, specifically: and (3) regarding the waveform from the first upper crossing zero point (namely the height of the previous point is less than 0, and the height of the previous point is more than or equal to 0) to the next upper crossing zero point as a complete wave, dividing the displacement information into a plurality of sections, extracting each wave, finding the highest value and the lowest value of each wave, calculating wave height data of the wave, and sequencing the single wave height data. Maximum wave period T corresponding to wave period information and wave height informationmaxIs the maximum wave height HmaxCorresponding to the wave period;
average period of top 1/10 maximum wave height;
average period of top 1/3 maximum wave height; t isavgIs the average wave period of all waves.
In step S4, wave direction information is determined according to the triaxial acceleration data of the wave. Specifically, a first-order kalman filter may be used to perform filtering processing on the triaxial acceleration data of the wave to obtain smooth triaxial acceleration data, which is used as the orthogonal component of the resultant acceleration vector, so as to ensure the robustness of the acceleration data. Then, fitting the projection track of the acceleration of the waves on the XY plane to obtain a fitted straight line in the relative direction of the waves; dividing a fitted straight line in the relative direction of the waves based on the average value of the projection tracks of the acceleration of the waves on the XY plane; determining the approximate position of the position point on the fitting straight line according to the slope of the fitting straight line and the position point of the upper zero crossing point position of each wave corresponding to the XY plane trajectory projection, and determining the direction of the wave relative to the self coordinate system of the acceleration sensor according to the position; and determining the absolute direction information of the waves according to the Euler angle of the Z axis, the included angle of the direction of the waves relative to the self coordinate system of the acceleration sensor on the Y axis and the magnetic declination of the data acquisition device where the acceleration sensor is positioned. Although the absolute direction information of a single wave is obtained, it is necessary to lock a predetermined area, divide the predetermined area into equal sections, and set the direction of the wave in the section with the largest number of waves as the direction information of the wave in the predetermined area.
In one embodiment, the wave direction information is an angle Dir ranging from 0 to 360 degrees with geographic north being 0 degrees, wherein the east direction is 90 degrees and the west direction is 270 degrees. The wave direction calculation can be divided into the following five steps:
1. filtering
Filtering the triaxial acceleration data by adopting a first-order Kalman filter to obtain smooth triaxial acceleration data serving as a resultant acceleration vector orthogonal component;
2. straight line fitting in opposite directions
Considering that the buoy can generate positive correlation inclination in the wave direction when fluctuating along with the waves, the xy plane of the ten-axis sensor can be approximately considered to be tangent to the convex surface of the waves. Therefore, for a certain sea wave, neglecting the rotation factor of the buoy, the projected locus of the combined acceleration vector on the xy plane of the sensor (i.e. only considering the acceleration data of the x axis and the y axis) should be linear during the movement of the buoy along with the sea wave. Before carrying out least square normal linear fitting on the track, whether the absolute value of the slope is greater than 1 or not needs to be judged through four points of the top, the bottom, the left and the right, linear fitting is carried out on the absolute value of the slope by adopting a corresponding least square method to obtain an exact slope k and an offset b, and the slope k is subjected to inverse trigonometric function operation to obtain a relative wave direction straight line which takes the ten-axis sensor as a reference system, but the straight line is non-directional and needs to be determined in a specific direction.
3. Straight line division in opposite directions
And (3) calculating the average value of the x axis and the average value of the y axis according to the projection track in the step (2) to obtain a gravity center, drawing a perpendicular line perpendicular to the straight line in the opposite direction obtained in the step (2) through the gravity center, and dividing the xy plane into two parts by taking the perpendicular line as a reference to finish the straight line division in the opposite direction.
4. Relative wave direction selection
All the upper crossing zeros are found based on the wave height waveform obtained when the wave height information is calculated. When the position of the upper zero crossing point is located, the buoy is located in the center of the wave, the highest point of the wave still does not pass through the buoy, the inclination angle of the buoy is the largest at the moment, and namely the xy plane projection point is the longest from the center of gravity. At this time, the projection point should be located on one of the two planes divided by the perpendicular bisector in step 3, and the position of the plane is the relative wave direction, so that the determination direction of the straight line relative to the wave direction in step 2 can be determined. Taking the positive direction of the y axis of the ten-axis sensor as relative 0 degree, and finally knowing the direction of the wave relative to the ten-axis sensor according to the slope k in the step 2 and the direction of the straight line in the step three (used for judging the quadrant).
5. Absolute wave direction calculation
And (3) according to the z-axis Euler angle data (namely the angle of the positive direction of the y-axis rotating to the north magnetic pole counterclockwise), the rotation angle of the reference frame of the current ten-axis module relative to the reference frame of the earth can be known. And (4) subtracting the z-axis Euler angle from the relative wave direction obtained in the step (4) to obtain the absolute wave direction of the relative geomagnetic north, and subtracting the geomagnetic declination of the sea area where the buoy is located to obtain the absolute wave direction of the relative geographic north. Wherein, the magnetic declination of the sea area is obtained by the GPS positioning result by looking up a table. Before outputting a result, the range of the angle is limited, so that the angle is finally within the range of 0-360 degrees.
6. Wave direction statistics
And (3) classifying the wave direction data obtained in the step 5, equally dividing 360 degrees into 16 directions according to 22.5 degrees as one class, and counting to obtain the direction with the highest frequency of occurrence as the final statistical wave direction.
According to the scheme, the acceleration data of the waves are subjected to integral processing through a frequency domain integral method to obtain frequency domain integral result data, so that an accumulated error generated when integral calculation displacement is caused by sampling noise is avoided, meanwhile, data fusion is carried out on the frequency domain integral result data, the resultant acceleration data and the air pressure data, the frequency domain integral result data are corrected, and accurate wave height information is obtained; and furthermore, wave period information can be accurately determined through the wave height information. According to the scheme, the wave direction identification method based on linear fitting and plane segmentation is adopted, and the absolute wave direction is calculated according to wave height zero-crossing data, vertical direction acceleration data and three-axis magnetic field data, so that the accuracy of wave direction information is improved.
As shown in fig. 6, the present solution further provides a wave data processing apparatus 101 implemented in cooperation with the wave data processing method, the apparatus including: an integration module 102, a fusion module 103, a wave period calculation module 104, and a wave direction calculation module 105. When the device works, firstly, the integral module 102 carries out frequency domain integral processing on the resultant acceleration data of the triaxial acceleration of the wave to obtain integral result data; then, the fusion module 103 performs data fusion on the integration result data, the resultant acceleration data and the air pressure data to obtain wave height information; then, the wave period calculation module 104 is used for determining wave period information according to the height information of the waves; finally, wave direction information is determined by the wave direction calculation module 105 according to the triaxial acceleration data of the waves.
In this embodiment, the correction module 106 may be configured in the apparatus, and the correction module 106 may perform data correction processing on the triaxial acceleration data and/or the magnetic field data of the wave.
In this scheme, when performing frequency domain integration processing on the combined acceleration data of the triaxial accelerations of the waves, the integration module 102 may first perform fast fourier transform on a time domain data set composed of the combined accelerations of the triaxial accelerations within a certain period of time by using a first transform unit to obtain a frequency domain data set; then, a second transformation unit is utilized to sequentially carry out frequency domain integration, integral phase transformation and integral frequency domain transformation on the frequency domain data set to obtain an integrated frequency domain data set; then, carrying out frequency domain filtering processing on the integrated frequency domain data set by using a filtering unit to obtain a filtered frequency domain data set; and finally, performing inverse Fourier transform processing on the filtered frequency domain data group by using an inverse transform unit to obtain integral result data.
In the scheme, when the fusion module 103 performs data fusion on the integration result data, the combined acceleration data and the air pressure data, a state transfer equation can be determined by using a first determining unit according to a secondary integration relation between acceleration and displacement; then, determining an observation equation by using a second determining unit according to the functional relation between the wave height and the air pressure; and finally, fusing to obtain a height value in the optimal state estimation, namely wave height information, by utilizing a fusion unit based on a state transition equation and an observation equation and utilizing a Kalman filtering data fusion algorithm.
In the scheme, when the wave period calculation module 104 determines the wave period information according to the height information of the waves, the searching unit can be used for determining the upper span zero point information of the waves in the time data set of the wave height; then, screening the zero crossing position meeting the constraint condition by using a screening unit according to the predetermined constraint condition; then, extracting a single wave by using the upper span zero point position as a dividing point by using an extraction unit; then, the traversing unit traverses each wave to determine the peak-valley value of each wave; and finally, determining the period information of the waves by using a period calculation unit according to the height information and the peak-to-valley value of each wave.
According to the scheme, when the wave direction calculation module 105 determines wave direction information according to the triaxial acceleration data of the waves, the preprocessing unit can be used for filtering the triaxial acceleration data of the waves to obtain smooth triaxial acceleration data which is used as an orthogonal component of a resultant acceleration vector, so that the robustness of the acceleration data is ensured. Then, fitting the projection track of the acceleration of the waves on the XY plane by using a fitting unit to obtain a fitted straight line in the relative direction of the waves; dividing the fitted straight line in the relative direction of the waves by using a dividing unit based on the average value of the projection tracks of the acceleration of the waves on the XY plane; determining the approximate position of the position point on the fitting straight line by using a relative direction calculation unit according to the slope of the fitting straight line and the position point of the XY plane trajectory projection corresponding to the upper span zero point position of each wave, and determining the direction of the wave relative to the self coordinate system of the acceleration sensor according to the position; determining absolute direction information of the waves by using an absolute direction calculation unit according to an Euler angle of a Z axis, an included angle of the direction of the waves relative to a coordinate system of an acceleration sensor and the Y axis, and a magnetic declination angle of a data acquisition device where the acceleration sensor is located; and finally, dividing the preset area into equal intervals by using a statistical unit, and taking the direction of the wave in the interval with the maximum number of waves as final wave direction information.
It should be understood that the units or modules in the present solution can be implemented by hardware, software, firmware or a combination thereof. In the above embodiments, the various steps or methods may be implemented in software or firmware stored in memory and executed by a suitable instruction execution system. For example, a discrete logic circuit having a logic Gate circuit for implementing a logic function on a data signal, an application specific integrated circuit having an appropriate combinational logic Gate circuit, a Programmable Gate Array (PGA), a Field Programmable Gate Array (FPGA), or the like is used.
On the basis of the wave data processing method, the scheme further provides a computer readable storage medium. The computer-readable storage medium is a program product for implementing the above-described data acquisition method, which may employ a portable compact disc read only memory (CD-ROM) and include program code, and may be run on a device, such as a personal computer. However, the program product of the present solution is not limited thereto, and in this document, a readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device.
The program product may employ any combination of one or more readable media. The readable medium may be a readable signal medium or a readable storage medium. A readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the foregoing. More specific examples (a non-exhaustive list) of the readable storage medium include: an electrical connection having one or more wires, a portable disk, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.
A computer readable storage medium may include a propagated data signal with readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated data signal may take many forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A readable signal medium may also be any readable medium that is not a readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device.
Program code embodied on a computer readable storage medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.
Program code for carrying out operations for aspects of the present invention may be written in any combination of one or more programming languages, including an object oriented programming language such as Java, C + + or the like and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user computing device, partly on a remote computing device, or entirely on the remote computing device or server. In the case of a remote computing device, the remote computing device may be connected to the user computing device through any kind of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or may be connected to an external computing device (e.g., through the internet using an internet service provider).
On the basis of the embodiment of the wave data processing method, the scheme further provides electronic equipment. The electronic device shown in fig. 7 is only an example, and should not bring any limitation to the functions and the scope of use of the embodiments of the present invention.
As shown in fig. 7, the electronic device 201 is in the form of a general purpose computing device. The components of the electronic device 201 may include, but are not limited to: at least one memory module 202, at least one processing module 203, a display module 204, and a bus 205 for connecting the various system components.
Wherein the storage module 202 stores program code that is executable by the processing module 203 such that the processing module 203 performs the steps of the various exemplary embodiments described in the wave data processing method above. For example, the processing module 203 may perform the steps as shown in fig. 1.
The memory module 202 may include a volatile memory module, such as a random access memory module (RAM) and/or a cache memory module, and may further include a read only memory module (ROM).
The storage module 202 may also include programs/utilities having program elements including, but not limited to: an operating system, one or more application programs, other program elements, and program data, each of which, or some combination thereof, may comprise an implementation of a network environment.
The bus 205 may include a data bus, an address bus, and a control bus.
The electronic device 201 may also communicate with one or more external devices 207 (e.g., keyboard, pointing device, bluetooth device, etc.), which may be through an input/output (I/O) interface 206. It should be appreciated that although not shown in the figures, other hardware and/or software elements may be used in conjunction with the electronic device 201, including but not limited to: microcode, device drivers, redundant processing modules, external disk drive arrays, RAID systems, tape drives, and data backup storage systems, among others.
The present solution is further illustrated by the following examples.
In this example, the wave data may be collected by a buoy having a ten-axis sensor mounted thereon. Triaxial acceleration data of waves are obtained by utilizing a triaxial accelerometer of a ten-axis sensor.
In order to reduce the displacement integral accumulated error caused by acceleration linear deviation and correct magnetic field linear deviation in the data acquisition process of the ten-axis sensor, the acceleration and magnetic field data are linearly corrected by adopting a least square method, the acceleration data are symmetrical about a zero point, the average value of X, Y axis acceleration is 0 when the acceleration data are horizontally placed, the average value of z axis acceleration is 1 (unit is g), and the central point of a magnetic field is located at the origin of coordinates of the ten-axis sensor.
Performing frequency domain integration processing on the resultant acceleration data of the triaxial acceleration based on the corrected acceleration data, specifically:
in a first step, a frequency domain data set is calculated. And setting the sampling frequency of the ten-axis sensor as sf, and recording the three-axis acceleration in a period of time. And calculating the total acceleration value of the corrected three-axis acceleration to serve as a time domain data set. And performing fast Fourier transform on the time domain data set to obtain a corresponding combined acceleration frequency domain data set, wherein the length nfft of a frequency domain array required by the fast Fourier transform is set to be a power of 2, and the frequency interval of the frequency domain array can be calculated
According to the Fourier transform formula
Converting the resultant acceleration time domain array to the frequency domain and obtaining the correlation
A symmetric frequency domain array;
step two, according to a frequency domain integral formula:
calculating a discrete circular frequency vector omeganAnd (4) array. Deriving the angular frequency interval d ω 2 π df, ω from the frequency interval dfnThe array calculation mode is as follows:
where n is the number of integrations.
And thirdly, integrating phase transformation. According to the frequency domain integration formula stated in the second step, the divided imaginary number unit j is integrated each time, namely, the rotation is performed by 90 degrees clockwise. The phase transformation formula is:
wherein real (F)i) Is FiReal part of, imag (F)i) Is FiAn imaginary part of (d);
and fourthly, integrating frequency domain transformation. The result of the third step after phase transformation is divided by omega in turnnArray of elements
And fifthly, filtering the frequency domain rectangular window. The frequency domain array F' obtained after the integration in the fourth stepiFiltering (namely, point multiplication of a window function and a frequency domain array, suppression of signals outside a frequency band required by the frequency domain array, and reservation or reinforcement of signals inside the required frequency band) is performed, wherein the window function adopted by the filtering is a rectangular window, and the calculation formulas of the low-pass frequency point and the high-pass frequency point are respectively as follows:
where Fmin is the low-pass cutoff frequency and Fmax is the high-pass cutoff frequency.
And sixthly, returning to the time domain to obtain integral. According to the inverse Fourier transform function
And returning the frequency domain array obtained in the fifth step to the time domain through inverse Fourier transform to obtain a final integration result f (t) ".
As shown in fig. 8, the wave height waveform shown in fig. 9 can be obtained by converting the time-domain three-axis combined acceleration into a frequency-domain data set after frequency domain transformation and performing frequency-domain integration and frequency-domain rectangular window filtering on the frequency-domain data set, and compared with the combined acceleration data shown in fig. 9, the wave height waveform has no obvious offset component (i.e., the average value is about 0) and the combined acceleration has a more obvious downward offset component (i.e., the average value is less than 0), so that the accumulated error of the acceleration is eliminated through the frequency-domain integration, and a more ideal curve of the wave height changing with time is obtained. However, while the accumulated error is eliminated, the data has an eye diagram effect, which affects the accuracy of the frequency domain integration result.
In order to further improve the accuracy of the frequency domain integration result data and further obtain accurate information of the final wave height along with the time change, the frequency domain integration result data, the acceleration value and the air pressure value can be subjected to Kalman data fusion. Specifically, the method comprises the following steps:
according to a linear discrete system state equation:
Y(k)＝HX(k)+V(k)
in the present system, there is no control quantity, i.e. the bu (k) term is 0, and Γ w (k) is also 0 regardless of the influence of noise, and from the quadratic integral relationship between acceleration and displacement, the state transition equation is obtained as:
by using the state transition equation, the three quantities that can be directly or indirectly observed are the acceleration, the frequency domain integrated altitude, and the barometric calculated altitude, respectively.
According to the formula of air pressure-wave height
Wherein R, Tm, g are all predetermined constants, and ln function is approximate to linear value when altitude variation is small, therefore, the relationship between air pressure and altitude obtained after simplification is:
from this, the observation equation can be found as:
therefore, the temperature of the molten metal is controlled,
substituting it into a Kalman data fusion formula:
the process error Q is generally obtained by multiplying the identity matrix by a small value such as 0.001, and R is a measurement error, which can be estimated by referring to a sensor data manual or after multiple measurements.
And the height value in the optimal state estimation obtained through Kalman data fusion is the wave height generated by the final data fusion.
As shown in fig. 10, the eye pattern effect in fig. 9 was significantly reduced after fusion.
After accurate wave height information is obtained, the period information of the waves can be further calculated according to the height information. When calculating the wave period, four wave height information are required to be calculated: maximum wave height HmaxFront 1/10 wave height
Front 1/3 wave height
And wave heightMean value Havg. Specifically, the method comprises the following steps:
and firstly, finding all the upper crossing zero points according to the obtained data set of the wave displacement information. Because the direct current component has been filtered out in the frequency domain integration processing process, the average value of the data set of the wave displacement information is about 0, when the zero crossing point is searched, the wave height trend item does not need to be calculated, and the zero crossing point is the intersection point of f (t) and the x axis. In the discrete case, the upper zero crossing point judgment condition is f (k-1) <0& & f (k) ≧ 0, all upper zero crossing point positions (i.e. k values) are found according to the condition and stored as an array ucp (up-cross points). As shown in fig. 9, the intersection point of the curve and the x-axis is the upper and lower zero crossing points, and the upper zero crossing point position is marked in fig. 9.
Taking all the upper span zero point positions as dividing points, and extracting a single wave WiTraversing each wave, finding the peak-valley value of the wave, and recording the peak-valley value as Wimax、WiminThen wave WiHas the height of:
Hi＝Wimax-Wimin
wave WiThe period of (A) is as follows:
for wave height HiSorting is carried out, and the maximum wave height H can be obtainedmax Front 1/10 maximum wave height average
Front 1/3 maximum wave height
Mean value and mean wave height HavgAnd corresponding wave period Tmax、
And Tavg。
Further, in conjunction with the data shown in fig. 11, the process of calculating the wave direction is as follows:
the first step, kalman filtering. In order to reduce the random jitter of the acceleration data and ensure the trend of the acceleration data, the kalman filter adopts a first-order retainer, and the estimated value is as follows:
x(k)＝x(k-1)+[x(k-1)-x(k-2)]
the response speed of the Kalman filter is improved by introducing a differential term [ x (k-1) -x (k-2) ], and the change trend of the acceleration track is prevented from being lost. The xy-axis acceleration data is filtered using this kalman filter, and an xy-plane acceleration trajectory (i.e., a projection trajectory of the resultant acceleration on the xy plane) indicated by a thin solid line is obtained as shown in fig. 11.
And secondly, fitting straight lines in opposite directions. Based on the xy plane projection track obtained in the first step, linear fitting is carried out by adopting a least square method, a fitting straight line function of the projection track is set as y-kx + b, and each point (x) of the track is seti,yi) The sum of the squared deviations to the fitted line is:
to make err2And (3) minimum, respectively solving partial derivatives of k and b to obtain an equation set:
finishing to obtain:
order to
Then
After k and b are calculated, a fitting straight line in the wave direction can be obtained, as shown by a dotted line in fig. 11.
And thirdly, linearly dividing the opposite direction. To determine the specific incoming and outgoing directions of the waves, the plane is divided into two parts by the vertical line passing through the center of gravity, and the center of gravity is calculated (i.e. the average value of the projected trajectories)
Wherein
Substituting the center of gravity into the vertical line
In (1), is calculated to obtain
The vertical line through the center of gravity is shown in bold solid lines in fig. 7.
And fourthly, selecting relative wave direction. Based on the upper span zero point array ucp obtained when the wave height information is calculated. Find each wave WiThe projection position of the xy plane track corresponding to the upper zero crossing position is recorded as uxiAnd uyiAccording to whether the absolute value of the slope k of the fitting straight line is less than 1 or not, the value of ux is determinediOr uyiSubstituting the point into the fitted straight line to obtain the approximate projection (sx) of the point on the fitted straight linei,syi) As indicated by the open circles in fig. 11. Finally, the moving direction of the wave relative to the coordinate system of the ten-axis sensor can be determined by judging which side of the vertical line the projection point is positioned on.
And fifthly, calculating the absolute wave direction. The direction of the magnetic north pole is known according to the absolute wave direction, and the z-axis Euler angle theta can be obtained according to the three-axis magnetic field and the three-axis angular velocity data of the ten-axis sensorzThe angle isThe y-axis is the reference axis and the z-axis is the rotation axis, the rotation angle of the sensor with respect to the magnetic north pole, as shown by the solid dots in FIG. 7. Therefore, given the relative wave heading and the north pole of the magnetic field, the absolute wave direction can be calculated. The slope k of the straight line in the wave direction is obtained in the second step, and the specific quadrant is determined in the fourth step, so that the included angle theta between the opposite wave direction and the positive direction of the y axis can be calculated through an inverse trigonometric function arctan0. According to the GPS positioning information, the latitude and longitude of the sea area where the current buoy is located can be determined, and the magnetic declination theta of the current buoy position can be known by inquiring a magnetic declination table in the SD cardoffset. The final wave absolute direction calculation formula is:
θ＝θ0-θz+θoffset
further limiting the calculated theta within the interval of 0,360) to finally obtain the wave WiIn the direction of (a).
And sixthly, counting wave directions. Dividing the direction of [0,360) into 16 equal parts, wherein each interval is 22.5 degrees, judging the directions of all waves, and selecting the interval with the largest number of waves as the wave direction calculation result.
Compared with the prior art, the scheme has higher processing speed and higher result precision, thereby facilitating ships, ground stations and the like to quickly and accurately acquire the wave information of the predetermined area.
As will be appreciated by one skilled in the art, embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
It should be understood that the above-mentioned embodiments of the present invention are only examples for clearly illustrating the present invention, and are not intended to limit the embodiments of the present invention, and it will be obvious to those skilled in the art that other variations or modifications may be made on the basis of the above description, and all embodiments may not be exhaustive, and all obvious variations or modifications may be included within the scope of the present invention.
Claims (22)
1. A wave data processing method, characterized in that the steps of the method comprise:
carrying out frequency domain integration processing on the resultant acceleration data of the triaxial acceleration of the waves to obtain integration result data;
and carrying out data fusion on the integration result data, the resultant acceleration data and the air pressure data to obtain wave height information.
2. The method of claim 1, wherein the frequency domain integration processing of the wave acceleration data to obtain integration result data comprises:
and carrying out data correction processing on the triaxial acceleration data and/or the magnetic field data of the waves.
3. The method of claim 1, wherein the step of performing frequency domain integration processing on the resultant acceleration data of the three-axis acceleration of the wave to obtain integration result data comprises:
performing fast Fourier transform on a time domain data set consisting of the combined acceleration of the three-axis acceleration within a certain period of time to obtain a frequency domain data set;
sequentially carrying out frequency domain integration, integration phase transformation and integration frequency domain transformation on the frequency domain data set to obtain an integrated frequency domain data set;
carrying out frequency domain filtering processing on the integrated frequency domain data set to obtain a filtered frequency domain data set;
and carrying out inverse Fourier transform processing on the filtered frequency domain data group to obtain integral result data.
4. The method of any one of claims 1 to 3, wherein the step of data fusing the integration result data, the resultant acceleration data and the air pressure data to obtain wave height information comprises:
determining a state transition equation according to a quadratic integral relation between the acceleration and the displacement;
determining an observation equation according to a functional relation between the wave height and the air pressure;
and based on a state transition equation and an observation equation, fusing to obtain a height value in the optimal state estimation, namely wave height information, by using a Kalman filtering data fusion algorithm.
5. The method of claim 4, wherein the method further comprises the steps of: wave period information is determined from the height information of the waves.
6. The method of claim 5, wherein the step of determining wave period information from the height information of the waves comprises:
determining the zero crossing point information of the waves according to the data set of the wave displacement information;
screening the upper span zero point position which accords with the constraint condition according to the predetermined constraint condition;
taking the upper span zero point position as a dividing point, and extracting a single wave;
traversing each wave, and determining the peak-valley value of each wave;
and determining the period information of the waves according to the height information and the peak-valley value of each wave.
7. The method of claim 1, wherein the method further comprises the steps of: and determining wave direction information according to the triaxial acceleration data of the waves.
8. The method of claim 7, wherein the step of determining wave direction information from the three-axis acceleration of the wave comprises:
fitting the projection track of the acceleration of the waves on the XY plane to obtain a fitted straight line of the relative direction information of the waves;
dividing a fitted straight line in the relative direction of the waves based on the average value of the projection tracks of the acceleration of the waves on the XY plane;
determining the approximate position of the position point on the fitting straight line according to the slope of the fitting straight line and the position point of the upper zero crossing point position of each wave corresponding to the XY plane trajectory projection, and determining the direction of the wave relative to the self coordinate system of the acceleration sensor according to the position;
and determining the absolute direction information of the waves according to the Euler angle of the Z axis, the included angle of the direction of the waves relative to the self coordinate system of the acceleration sensor on the Y axis and the magnetic declination of the data acquisition device where the acceleration sensor is positioned.
9. The method of claim 8, wherein the step of determining wave direction information from the three-axis acceleration of the wave further comprises:
and equally dividing the preset area into intervals, and taking the direction of the wave in the interval with the maximum number of waves as final wave direction information.
10. The method according to claim 8, wherein the fitting process of the projected trajectory of the acceleration of the wave on the XY plane, and the previous step of obtaining the fitted straight line of the projected trajectory comprises:
and filtering the triaxial acceleration data of the waves to obtain smooth triaxial acceleration data.
11. A wave data processing apparatus, characterized in that the apparatus comprises:
the integration module is used for carrying out frequency domain integration processing on the combined acceleration data of the triaxial acceleration of the waves to obtain integration result data;
and the fusion module is used for carrying out data fusion on the integral result data, the resultant acceleration data and the air pressure data to obtain wave height information.
12. The apparatus of claim 11, further comprising:
and the correction module is used for carrying out data correction processing on the triaxial acceleration data and/or the magnetic field data of the waves.
13. The apparatus of claim 11, wherein the integration module comprises:
the first transformation unit is used for carrying out fast Fourier transformation on a time domain data set formed by the combined acceleration of the three-axis acceleration within a certain period of time to obtain a frequency domain data set;
the second transformation unit is used for sequentially carrying out frequency domain integration, integration phase transformation and integration frequency domain transformation on the frequency domain data set to obtain an integrated frequency domain data set;
the filtering unit is used for carrying out frequency domain filtering processing on the frequency domain data set after integration to obtain a filtered frequency domain data set;
and the inverse transformation unit is used for carrying out inverse Fourier transformation on the filtered frequency domain data group to obtain integral result data.
14. The apparatus of any one of claims 11 to 13, wherein the fusion module comprises:
the first determining unit is used for determining a state transition equation according to a quadratic integral relation between the acceleration and the displacement;
the second determining unit determines an observation equation according to the functional relation between the wave height and the air pressure;
and the fusion unit is used for fusing to obtain a height value in the optimal state estimation, namely wave height information, by using a Kalman filtering data fusion algorithm based on a state transition equation and an observation equation.
15. The apparatus of claim 11, further comprising:
and the wave period calculation module is used for determining wave period information according to the height information of the waves.
16. The apparatus of claim 15, wherein the wave period calculation module comprises:
the searching unit is used for determining the upper crossing zero point information of the waves in the time data set of the wave height;
the screening unit screens the upper span zero point position which accords with the constraint condition according to the predetermined constraint condition;
the extraction unit is used for extracting a single wave by taking the upper span zero point position as a dividing point;
the traversing unit is used for traversing each wave and determining the peak-valley value of each wave;
and the period calculating unit is used for determining the period information of the waves according to the height information and the peak-to-valley value of each wave.
17. The apparatus of claim 11, further comprising:
and the wave direction calculation module is used for determining wave direction information according to the triaxial acceleration data of the waves.
18. The apparatus of claim 17, wherein the wave direction calculation module comprises:
the fitting unit is used for fitting the projection track of the acceleration of the waves on the XY plane to obtain a fitted straight line of the relative direction information of the waves;
the dividing unit is used for dividing the fitting straight line in the relative direction of the waves on the basis of the average value of the projection tracks of the acceleration of the waves on the XY plane;
the relative direction calculating unit is used for determining the approximate position of the position point on the fitting straight line according to the slope of the fitting straight line and the position point of the upper span zero point position of each wave corresponding to the XY plane track projection, and determining the direction of the wave relative to the self coordinate system of the acceleration sensor according to the position;
and the absolute direction calculating unit determines the absolute direction information of the waves according to the Euler angle of the Z axis, the included angle of the direction of the waves relative to the self coordinate system of the acceleration sensor on the Y axis and the magnetic declination angle of the data acquisition device where the acceleration sensor is positioned.
19. The apparatus of claim 18, wherein the wave direction calculation module further comprises:
and the statistical unit is used for dividing the preset area into equal intervals and taking the direction of the wave in the interval with the maximum number of waves as final wave direction information.
20. The apparatus of claim 19, wherein the wave direction calculation module further comprises:
and the preprocessing unit is used for filtering the triaxial acceleration data of the waves to obtain smooth triaxial acceleration data.
21. An apparatus, comprising: a memory, one or more processors; the memory is connected with the processor through a communication bus; the processor is configured to execute instructions in the memory; the storage medium has stored therein instructions for carrying out the steps of the method according to any one of claims 1 to 10.
22. A computer-readable storage medium, on which a computer program is stored which, when being executed by a processor, carries out the steps of the method according to any one of claims 1 to 10.
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