Offshore profile wind speed motion compensation method and system

Abstract

The invention belongs to the field of marine meteorological intelligent sensing observation, and particularly relates to an offshore profile wind speed motion compensation method and system, and the method comprises the following steps: S1, carrying out the wind speed measurement through an ultrasonic wind speed sensor under an ideal working condition; s2, dividing the motion state of the observation platform such as the offshore buoy into three dimensions of rolling, pitching and heaving, and establishing a three-dimensional space coordinate system; s3, building a measuring platform, and respectively simulating rolling and pitching motions of the sensor by controlling the motion of the holder in the left-right direction and the front-back direction; and S4, acquiring real sea surface wind speed data, and performing algorithm compensation on the wind speed data measured by the sensor. The method has the advantages that wind speed data measured in different transverse inclination and longitudinal inclination states can be corrected, the influence of platform movement on wind speed measurement is effectively compensated, and the accuracy of wind speed measurement is improved.

Description

Technical Field

[0001] The present invention belongs to the field of marine meteorological intelligent perception observation, and specifically relates to a method and system for compensating for offshore profile wind speed motion. Background Art

[0002] Wind speed refers to the speed at which the outside air flows relative to a fixed point on the earth, that is, the measurement value of the anemometer in a static state is the true wind speed of the environment. Common wind speed measurement methods include mechanical wind measurement, thermal wind measurement, and ultrasonic wind measurement. Among them, mechanical wind measurement and thermal wind measurement have the advantages of simple measurement principle and convenient operation, but the equipment is easily affected by external environmental factors, and has the disadvantages of low measurement accuracy and poor reliability. With the development of sensor technology, ultrasonic wind sensors made of micro-electromechanical technology have overcome the defects of traditional wind speed meters. By measuring the pulse time difference between the transmitting end and the receiving end, Doppler transformation is performed to achieve wind speed measurement, thereby improving the accuracy of wind speed measurement.

[0003] Wind speed measurement is crucial to refined meteorological forecasts. In the field of marine meteorological observation, when offshore buoys, ships and other observation platforms are conducting wind speed measurement operations, the observation platforms are swayed and shaken by the combined effects of factors such as sea breeze, waves and currents. The anemometer installed on the observation platform moves with the movement of the platform, and the wind speed data measured includes the platform's own movement data. The wind speed data has errors and cannot meet the requirements for accurate measurement of ocean wind speed. Summary of the invention

[0004] In order to solve the problems existing in the above-mentioned background technology, the present invention provides an offshore profile wind speed motion compensation algorithm to obtain true and accurate sea surface wind speed data.

[0005] In order to achieve the above object, the present invention adopts the following technical solution: an offshore profile wind speed motion compensation algorithm, comprising the following steps:

[0006] S1. Wind speed measurement by ultrasonic wind speed sensor under ideal working conditions;

[0007] S2. The motion state of the observation platform such as the offshore buoy is divided into three dimensions: roll, pitch and heave, and a three-dimensional space coordinate system is established;

[0008] S3. Build a measurement platform and simulate the roll and pitch motion of the sensor by controlling the movement of the gimbal in the left and right and front and back directions;

[0009] S4. Obtain the real sea surface wind speed data and perform algorithm compensation on the wind speed data measured by the sensor.

[0010] Preferably, in step S1, under ideal working conditions, the sensor wind duct and the external wind field are in the same horizontal plane, and under the action of the external wind, the ultrasonic wave is transmitted from A to 1 Transfer to A 2 The time is t 1 , from A 2 Transfer to A 1 The time is t 2 , the distance between the sensors is S, and the ultrasonic propagation speed is V 1 , the external wind speed is V 2 , the incident angle and reflection angle between the ultrasonic wave and the wind field are both θ, and the following relationship is obtained:

[0011]

[0012] The time difference between the transmission of ultrasonic waves at two sensors is Δt, and the relationship is as follows:

[0013]

[0014] Since the ultrasonic wave propagation speed V 1 Much greater than wind speed V 2 , the range of the cosθ function is [-1, 1]. Simplifying the above formula, we can get:

[0015]

[0016] By calculating the time difference between the transmission of ultrasonic waves between the two sensors, the current wind speed value can be calculated.

[0017] Preferably, in step S2, the x-axis is defined as the left-right rolling direction, the y-axis is defined as the front-back pitching direction, and the z-axis is defined as the up-down heave direction, and a three-dimensional space coordinate system is established:

[0018] In the S2.1 rolling state, the sensor moves left and right along the x-axis, the angle between the wind field plane and the sensor wind duct is α, and the initial wind speed motion component is OA 1 , the calculation formula of wind speed OA under rolling state is:

[0019]

[0020] In the S2.2 pitch state, the sensor moves forward and backward along the y-axis, the angle between the wind field plane and the sensor wind duct is β, and the initial wind speed motion component is OB 1 , the calculation formula of wind speed OB in pitch state is:

[0021]

[0022] S2.3 In the heave state, the sensor moves up and down along the z-axis. In an ideal state, the sensor wind duct and the external wind field are considered to be in the same horizontal plane, and the influence of heave on the wind speed measurement error can be ignored. According to the offshore profile wind speed motion compensation algorithm described in claim 1, it is characterized in that a sensor roll motion platform is built, the direction and flow rate of the external wind field are fixed, and the sensor wind duct and the external wind field are in the same horizontal plane in the initial state;

[0023] Build a sensor pitch motion platform with fixed external wind direction and velocity. In the initial state, the sensor air duct and the external wind field are in the same horizontal plane.

[0024] Preferably, a high-order polynomial is used to fit the sensor inclination angle and wind speed measurement errors, and the relationship is as follows:

[0025]

[0026] In the formula, ΔV is the wind speed measurement error at the current inclination angle, Vγ is the actual wind speed outside, Vγ' is the wind speed value measured by the sensor at the current inclination angle, and P is the unknown coefficient. Therefore, the compensation for the sensor wind speed measurement error is converted into the coefficient P. The relationship between the coefficient P is as follows:

[0027]

[0028] The C matrix has m rows and n columns. By substituting k sets of wind speed data, we get the corresponding set of equations as follows:

[0029]

[0030] The solution of the polynomial is solved by the least square method to minimize the square error;

[0031]

[0032] ΔV=P 0 +P 1 γ+P 2 γ 2 +P 3 γ 3 +P 4 γ 4 +P 5 γ 5 +P 6 γ 6 +P 7 γ 7 +P 8 γ 8

[0033] Substituting the coefficient into the wind speed error calculation formula, the wind speed measurement value under the current state can be compensated.

[0034] An offshore profile wind speed motion compensation system comprises a data acquisition module, a data processing module and a data output module;

[0035] Data acquisition module: use sensors to obtain data information;

[0036] Data processing module: calculates the wind speed value under ideal working conditions and the wind speed value under simulation conditions;

[0037] Wind speed error compensation based on heel and pitch angles;

[0038] Data output model: wind speed measurement value under current conditions.

[0039] Compared with the prior art, the present invention has the following beneficial effects:

[0040] 1. The present invention analyzes the generation mechanism of wind speed measurement error in motion and uses a high-order polynomial fitting algorithm to compensate for it;

[0041] 2. The present invention can correct the wind speed data measured under different heel and pitch states, effectively compensate for the influence of platform movement on wind speed measurement, and improve the accuracy of wind speed measurement. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] Figure 1 This is the principle diagram of wind speed measurement using an ultrasonic anemometer under ideal working conditions.

[0043] Figure 2 This is the schematic diagram of the heel state error generation under actual working conditions.

[0044] Figure 3 This is the schematic diagram of the pitch state error under actual working conditions.

[0045] Figure 4 Comparative analysis of wind speed measurement data for heel state error algorithm.

[0046] Figure 5 Comparative analysis of wind speed measurement data for the pitch state error algorithm.

[0047] Figure 6 This is the flow chart of this application. DETAILED DESCRIPTION

[0048] In order to enable those skilled in the art to better understand the technical solution of the present invention, the present invention is further described below in conjunction with the accompanying drawings and specific implementation methods.

[0049] An offshore profile wind speed motion compensation algorithm comprises the following steps:

[0050] Step 1: Analysis of wind speed measurement principle of ultrasonic wind speed sensor under ideal working conditions;

[0051] Step 2: Define the three-dimensional motion coordinate system and analyze the motion state of the observation platform and the mechanism of wind speed error;

[0052] Step 3: Build a measurement platform to record wind speed measurement data at different heel angles and pitch angles;

[0053] Step 4: Establish an error compensation algorithm to solve the high-order polynomial solutions for different heel angles α and pitch angles β, compensate the wind speed data, and reduce the wind speed measurement error.

[0054] In the actual implementation process:

[0055] Step 1, take the ultrasonic wind sensor with integrated transceiver as an example. Figure 1 As shown in the figure, under ideal working conditions, the sensor wind duct and the external wind field are in the same horizontal plane. Under the action of external wind, the ultrasonic wave is transmitted from A to 1 Transfer to A 2 The time is t 1 , from A 2 Transfer to A 1 The time is t 2 , the distance between the sensors is S, and the ultrasonic propagation speed is V 1 , the external wind speed is V 2 , the incident angle and reflection angle between the ultrasonic wave and the wind field are both θ.

[0056] The following relationship is obtained:

[0057]

[0058] The time difference between the transmission of ultrasonic waves at two sensors is Δt, and the relationship is as follows:

[0059]

[0060] Since the ultrasonic wave propagation speed V 1 Much greater than wind speed V 2 , the range of the cosθ function is [-1, 1]. Simplifying the above formula, we can get:

[0061]

[0062] It can be seen from the above formula that by calculating the time difference of ultrasonic wave transmission between two sensors, the current wind speed value can be calculated.

[0063] Step 2: Under actual measurement conditions, observation platforms such as offshore buoys are swayed by external factors such as sea breeze and waves, causing the sensor wind duct to be not in the same horizontal plane as the external wind field. In a broad sense, the motion state of observation platforms such as offshore buoys is divided into three dimensions: roll, pitch and heave, and a three-dimensional spatial coordinate system is established.

[0064] The x-axis is defined as the left-right roll direction, the y-axis is defined as the front-back pitch direction, and the z-axis is defined as the up-down swing direction.

[0065] Step 2.1: In the rolling state, the sensor moves left and right along the x-axis, and the angle between the wind field plane and the sensor wind duct is α, as shown in Figure 2 shown.

[0066] The initial wind speed motion component is OA 1 , the calculation formula of wind speed OA under rolling state is:

[0067]

[0068] Step 2.2: In the pitch state, the sensor moves forward and backward along the y-axis, and the angle between the wind field plane and the sensor wind duct is β, as shown in Figure 3 shown.

[0069] The initial wind speed motion component is OB 1 , the calculation formula of wind speed OB in pitch state is:

[0070]

[0071] Step 2.3, in the heave state, the sensor moves up and down along the z-axis. Ideally, the sensor wind duct and the external wind field are considered to be in the same horizontal plane, so the effect of heave on the wind speed measurement error can be ignored.

[0072] In summary, by comparing the wind speed calculation formula under ideal conditions and actual measurement conditions, it is found that with the change of the spatial position of the sensor wind duct and the external wind field, an angle is formed between the sensor wind duct and the external wind field plane, and the calculated wind speed value changes with the angle, thus causing an actual measurement error of the wind speed.

[0073] Step 3: By analyzing the motion state of the buoy, it can be seen that the main factors causing the wind speed measurement error are the roll angle α and the pitch angle β. Therefore, a measurement platform is built to simulate the roll and pitch motion of the sensor by controlling the movement of the gimbal in the left and right and front and back directions.

[0074] Step 3.1, build the sensor rolling motion platform, the external wind field direction and flow rate are fixed, and the sensor wind duct is in the same horizontal plane as the external wind field in the initial state. Taking the right tilt as an example, the sensor is tilted to the right by 5°, 10°, 15°, 20°, and 25° through the PTZ, and a total of 8 groups of wind speed values ​​are measured, which are as follows:

[0075] Table 1 Wind speed values ​​measured when the sensor is tilted to the right (m / s)

[0076]

[0077] Step 3.2, build the sensor pitch motion platform, the external wind field direction and flow rate are fixed, and the sensor wind duct is in the same horizontal plane as the external wind field in the initial state. Taking the forward tilt as an example, the sensor is controlled by the PTZ to tilt forward at 5°, 10°, 15°, 20°, and 25°, and a total of 8 groups of wind speed values ​​are measured, which are as follows:

[0078] Table 2 Wind speed values ​​measured when the sensor is tilted forward (m / s)

[0079]

[0080]

[0081] By taking the average of each group of wind speed data and comparing them, it is found that the wind speed measurement data of the sensor changes when it is in the state of transverse tilt and longitudinal tilt. Among them, in the state of transverse tilt (taking right tilt as an example), the wind speed measurement error is 0.31-1.09m / s; in the state of longitudinal tilt (taking forward tilt as an example), the wind speed measurement error is 0.47-1.58m / s, and with the increase of the tilt angle, the wind speed measurement error increases significantly.

[0082] Step 4: To obtain the real sea surface wind speed data, the wind speed data measured by the sensor is compensated by algorithm.

[0083] Step 4.1, use a high-order polynomial to fit the sensor inclination angle and wind speed measurement errors, the relationship is as follows:

[0084]

[0085] Where ΔV is the wind speed measurement error at the current inclination angle, V γ is the real wind speed outside, V γ ' is the wind speed value measured by the sensor at the current inclination angle, and P is the unknown coefficient. Therefore, the compensation for the sensor wind speed measurement error is converted into solving the coefficient P. The relationship of the coefficient P is as follows:

[0086]

[0087] The C matrix has m rows and n columns, and matches the measured wind speed data to solve the wind speed measurement error. By substituting k sets of wind speed data, the corresponding equation group is obtained as follows:

[0088]

[0089] Solve the polynomial using the least squares method to minimize the square error. Select m = n = 8, then:

[0090]

[0091] ΔV=P 0 +P1 γ+P 2 γ 2 +P 3 γ 3 +P 4 γ 4 +P 5 γ 5 +P 6 γ 6 +P 7 γ 7 +P 8 γ 8

[0092] Substituting the coefficient into the wind speed error calculation formula, the wind speed measurement value under the current state can be compensated.

[0093] When the sensor is in the heel state, with the heel angle α as the state factor, the wind speed measurement error compensation relationship is as follows:

[0094] ΔV=P 0 +P 1 α+P 2 α 2 +P 3 α 3 +P 4 α 4 +P 5 α 5 +P 6 α 6 +P 7 α 7 +P 8 α 8

[0095] Solve the polynomial coefficient P and get P 1 =0.013, P 2 =0.027, P 3 =0.037, P 4 =0.051, P 5 =0.057, P 6 =0.063, P 7 =0.067, P 8 =0.083. Based on the wind speed error compensation algorithm, the compensated wind speed data is calculated as follows:

[0096] Table 3 Wind speed measurement error compensation of sensor in heel state

[0097]

[0098] When the sensor is in the pitch state, with the pitch angle β as the state factor, the wind speed measurement error compensation relationship is as follows:

[0099] ΔV=P 0 +P 1 β+P 2 β 2 +P 3 β 3 +P 4 β 4 +P 5 β 5 +P 6 β 6 +P 7 β 7 +P 8 β 8

[0100] Solve the polynomial coefficient P and get P 1 =0.021, P 2 =0.024, P 3 =0.034, P 4 =0.044, P 5 =0.051, P 6 =0.053, P 7 =0.077, P 8 =0.078. Based on the wind speed error compensation algorithm, the compensated wind speed data is as follows:

[0101] Table 4 Wind speed measurement error compensation of sensor in pitch state

[0102]

[0103] In summary, the wind speed data measured under the heel and pitch states are compensated based on the error compensation algorithm. Compared with the initial measurement data, the wind speed measurement error can be reduced, which proves the effectiveness of the error compensation algorithm.

Claims

1. An offshore profile wind speed motion compensation algorithm, characterized in that: The following steps are involved: S1. Wind speed measurement by ultrasonic wind speed sensor under ideal working conditions; S2. The motion state of the observation platform such as the offshore buoy is divided into three dimensions: roll, pitch and heave, and a three-dimensional space coordinate system is established; S3. Build a measurement platform and simulate the roll and pitch motion of the sensor by controlling the movement of the gimbal in the left and right and front and back directions; S4. Obtain the real sea surface wind speed data and perform algorithm compensation on the wind speed data measured by the sensor.

2. The offshore profile wind speed motion compensation algorithm according to claim 1, characterized in that: In step S1, under ideal working conditions, the sensor wind duct and the external wind field are in the same horizontal plane. Under the action of the external wind, the time for the ultrasonic wave to be transmitted from A1 to A2 is t1, and the time for the ultrasonic wave to be transmitted from A2 to A1 is t2. The distance between the sensors is S, the ultrasonic wave propagation speed is V1, the external wind speed is V2, and the incident angle and reflection angle between the ultrasonic wave and the wind field are both θ, and the following relationship is obtained: The time difference between the transmission of ultrasonic waves at two sensors is Δt, and the relationship is as follows: Since the ultrasonic propagation speed V1 is much greater than the wind speed V2, the range of the cosθ function is [-1, 1]. Simplifying the above formula, we can get: By calculating the time difference between the transmission of ultrasonic waves between the two sensors, the current wind speed value can be calculated.

3. The offshore profile wind speed motion compensation algorithm according to claim 1, characterized in that: In step S2, the x-axis is defined as the left-right roll direction, the y-axis is defined as the front-back pitch direction, and the z-axis is defined as the up-down swing direction, and a three-dimensional space coordinate system is established: In the S2.1 roll state, the sensor moves left and right along the x-axis. The angle between the wind field plane and the sensor wind duct is α. The initial wind speed motion component is OA1. The wind speed OA calculation formula in the roll state is: S2.2 In the pitch state, the sensor moves forward and backward along the y-axis, the angle between the wind field plane and the sensor wind duct is β, the initial wind speed motion component is OB1, and the wind speed OB calculation relationship in the pitch state is: In the S2.3 vertical swing state, the sensor moves up and down along the z-axis. Ideally, the sensor wind duct and the external wind field are considered to be in the same horizontal plane, and the influence of vertical swing on the wind speed measurement error can be ignored.

4. The offshore profile wind speed motion compensation algorithm according to claim 1, characterized in that: Build a sensor rolling motion platform, with the external wind field direction and flow rate fixed. In the initial state, the sensor air duct and the external wind field are in the same horizontal plane; Build a sensor pitch motion platform with fixed external wind direction and velocity. In the initial state, the sensor air duct and the external wind field are in the same horizontal plane.

5. The offshore profile wind speed motion compensation algorithm according to claim 1, characterized in that: A high-order polynomial is used to fit the sensor inclination angle and wind speed measurement errors, and the relationship is as follows: Where ΔV is the wind speed measurement error at the current inclination angle, V γ is the real wind speed outside, V γ ' is the wind speed value measured by the sensor at the current inclination angle, and P is the unknown coefficient. Therefore, the compensation for the sensor wind speed measurement error is converted into the coefficient P. The relationship of the coefficient P is as follows: The C matrix has m rows and n columns. By substituting k sets of wind speed data, we get the corresponding set of equations as follows: The solution of the polynomial is solved by the least square method to minimize the square error; Substituting the coefficient into the wind speed error calculation formula, the wind speed measurement value under the current state can be compensated.

6. An offshore profile wind speed motion compensation system, equipped with the offshore profile wind speed motion compensation method according to any one of claims 1 to 5, characterized in that: It includes a data acquisition module, a data processing module and a data output module; Data acquisition module: use sensors to obtain data information; Data processing module: calculates the wind speed value under ideal working conditions and the wind speed value under simulation conditions; Wind speed error compensation based on heel and pitch angles; Data output model: wind speed measurement value under current conditions.

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