Trestle active wave compensation method based on multi-sensor fusion positioning

Abstract

The invention provides a trestle active wave compensation method based on multi-sensor fusion positioning, and relates to the technical field of wave compensation of maritime work equipment, and the method specifically comprises the following steps: S1, collecting ship data of a laser radar, an inertial sensor I MU and a GPS positioning system, processing the ship data through improved Kalman filtering, and achieving marine precise positioning of a ship; s2, establishing a coordinate system, taking a ship as an initial state when the ship is lapped to a wind power tower at the tail end of a static underwater trestle, and establishing a rectangular coordinate system O by taking the rotation center of the ship as an original point; s3, according to the swaying, surging, yawing, rolling, pitching and heaving information, obtained by an attitude sensor MRU, of the ship at the instantaneous moment, the target position quantity of each joint of the trestle is calculated through motion attitude inverse solution; and S4, each joint is controlled to stably move to a target position, and wave compensation is completed. According to the invention, by designing the Kalman filtering system for multi-sensor fusion positioning, the position of the ship can be positioned more accurately, and the active wave compensation precision of the trestle can be improved.

Description

Technical Field

[0001] The invention relates to the technical field of wave compensation for marine engineering equipment, and in particular to an active wave compensation method for a pier based on multi-sensor fusion positioning. Background Art

[0002] Offshore wind power requires repair and regular maintenance, and a pier is needed to transport personnel to the offshore wind power platform. However, due to the influence of factors such as wind and waves, ships at sea will experience wave motion, which poses a safety hazard when transporting personnel. The pier needs to compensate for the wave motion of the ship through active wave compensation, so that the pier and the offshore wind power platform remain relatively static, making it convenient for personnel to board the wind power platform from the ship, and ensuring safety and accessibility of wind power operation and maintenance.

[0003] The pier generally has rotation, luffing and telescopic joints. During active waves, the ship needs to turn on DP and use dynamic positioning to make the end of the pier compensate for the ship's sway, pitch and bow pitch. The attitude sensor MRU is usually used to collect the ship's position and motion information, and the rotation, luffing and telescopic joints required at the end of the pier are calculated through attitude solution, and each joint is controlled to move to the corresponding position.

[0004] The accuracy of ship DP is usually 1.5 meters to 2 meters, while the compensation accuracy of the pier end needs to be within 20 cm. Therefore, simply relying on DP to compensate for the ship's sway and surge cannot meet the requirements of active wave compensation of the pier. Other methods are also needed to measure the residual sway and surge of the ship after DP compensation, and feed this information back to the pier control system. Finally, the pier end is compensated through the motion joint to improve the compensation accuracy. Summary of the invention

[0005] The purpose of the present invention is to provide an active wave compensation method for a pier based on multi-sensor fusion positioning. By designing a Kalman filter system of multi-sensor fusion positioning of an inertial sensor IMU, a GPS positioning system and a laser radar, the shortcomings of each sensor are complemented, and the method has the characteristics of high precision, long time and strong independence.

[0006] The above technical objectives of the present invention are achieved through the following technical solutions:

[0007] A method for active wave compensation of a pier based on multi-sensor fusion positioning specifically comprises the following steps:

[0008] S1. By collecting ship data from laser radar, inertial sensor IMU, and GPS positioning system, and using improved Kalman filtering to process ship data, accurate positioning of ships at sea can be achieved;

[0009] S2. Establish a coordinate system, taking the state when the ship is connected to the wind turbine tower at the end of the trestle under still water as the initial state, and establishing a rectangular coordinate system O with the rotation center of the ship at this time as the origin;

[0010] S3, the instantaneous sway, surge, pitch, roll, pitch and heave information of the ship is obtained through the attitude sensor MRU, and the motion attitude is inversely solved to calculate the target position of each joint of the pier, including the extension amount S of the telescopic joint, the rotation amount R of the slewing joint and the extension amount L of the luffing joint;

[0011] S4, control each joint to move smoothly to the target position to complete wave compensation;

[0012] In step S1, the position information of the ship traveling at sea is collected by the laser radar, inertial sensor IMU and GPS positioning system, and the output of the inertial sensor IMU is corrected by the filter through an indirect filtering method of filter output correction. The position and speed errors output by the inertial sensor IMU are used as the state vector of the loose combination system, and the difference of the tag position calculated by the GPS positioning system, the laser radar and the inertial sensor IMU is used as the measurement variable and input into the filter. Based on this, the discrete state space expression of the loose combination positioning system is established as follows: k =FX k-1 +W k-1 , Z k =HX k +V k , where X k and Z k k

[0013] The system state variables and test variables at the moment, F and H are the system state transfer matrix and system matrix respectively, W k-1 is the system process noise at time k-1, assuming its covariance is Q k , V k is the measurement noise at time k, assuming its covariance is R k .

[0014] Furthermore, in step S1, Among them, δP x ,δP y ,δP z They represent the position errors of the carrier on the X, Y, and Z axes respectively when the inertial sensor IMU is solved, δυ x ,δυ y ,δυ z They represent the velocity errors of the carrier solved by the inertial sensor IMU on the X, Y, and Z axes respectively; T is the sampling time interval, Indicates the position of the carrier in the X, Y, and Z axis directions calculated by the inertial sensor IMU. Indicates the position of the carrier in the X, Y, and Z axis directions calculated by the GPS positioning system. Indicates the position of the laser radar solution carrier in the X, Y, and Z axis directions.

[0015] Furthermore, in step S1, the initial state value X is given 0 , initial value of covariance matrix P 0 According to the KF algorithm, the optimal estimated value of the positioning error at each sampling time can be estimated. The KF equation is as follows: The state one-step prediction is The covariance one-step forecast is P k|k-1 =FP k-1|k-1 F T +Q k , the filter gain is K k =P k|k-1 H T (HP k|k-1 H T +R k ) -1 , the final sensor state estimate is The ship position can be obtained and the covariance is updated to P k+1|k+1 =P k|k-1 -K k HP k|k-1 ; Among them, k|k-1 represents the value of point k-1 at time k, k-1|k-1 represents the value of point k-1 at time k-1, k|k represents the value of point k at time k, and k+1|k+1 represents the value of point k+1 at time k+1.

[0016] Furthermore, in step S1, Where Q Px , Q Py , Q Pz are the covariance of the position error of the carrier on the x, y, and z axes respectively solved by the inertial sensor IMU, υx , Q υy , Q υz They are the covariance of the velocity error of the carrier on the x, y, and z axes respectively calculated by the inertial sensor IMU.

[0017] Furthermore, in step S1, In but

[0018]

[0019] Furthermore, in step S2, the Kalman filter is used to calculate The position of the ship is obtained, and the position of the fixed object target point C of the wind turbine tower, the position of the end position of the trestle point A, the position of the trestle rotation center point B, and the positions of the trestle variable amplitude joint connection points D and E are obtained through the trestle structure; the coordinate system is established with the center of gravity of the ship in the initial state as the coordinate origin O(0, 0, 0), and the coordinate conversion between the ship position and point O calculated by Kalman filtering is obtained to obtain the coordinate positions of points A, B, C, D and E in the O coordinate system, and the position of the fixed object target point C of the wind turbine tower in the initial state coincides with the position of the end position of the trestle point A; among them, the coordinates of the fixed object target point C of the trestle wind turbine tower are (C x , C y , C z ), the coordinates of point A at the end of the trestle are (A x , A y , A z ), the coordinates of point B at the trestle rotation center are (B x , B y , B z ), the coordinates of point D and point E at the trestle variable-length joint connection position are (D x , D y , D z ) and (E x , E y , E z ).

[0020] Furthermore, in step S3, the angular changes (x1, y1, z1) of the sway, pitch and pitch of the trestle on the x, y and z axes, and the displacement changes (x2, y2, z2) of the trestle on the x, y and z axes are measured by the MRU attitude sensor to obtain the rotation matrix M and translation matrix T of the trestle motion, where:

[0021] Furthermore, in step S3, the coordinates of the terminal position A' of the pier and the rotation center position B' of the pier after the wave movement can be obtained according to the rotation matrix M and the translation matrix T, where the coordinates of point A' are (A' x , A' y , A' z ), the coordinates of point B' are (B' x , B' y , B' z ),but

[0022] Furthermore, in step S3, the extension amount S required for active wave compensation of the pier, the rotation amount R of the slewing joint and the extension amount L of the variable amplitude cylinder can be obtained through the coordinates of the terminal position A' and the rotation center position B' after the wave movement, wherein:

[0023] And I = GN × p, where G = [(D x -B x ) 2 +(D y -B y ) 2 +(D z -B z ) 2 ]+[(E x -B x ) 2 +(E y -B y ) 2 +(E z -B z ) 2 ],N=2[(D x -B x )×(E x -B x )+(D y -B y )×(E y -B y )+(D z -B z )×(E z -B z )],

[0024] Furthermore, in the step S1, the inertial sensor IMU is installed on the ship deck to sense the acceleration, tilt, impact, vibration, rotation and multi-degree-of-freedom motion of the ship; the GPS positioning system is installed on the ship deck to accurately locate the position of the ship; the laser radar is set at the end of the pier to sense the positional relationship between the end of the pier and the target connection; in the step S3, the attitude sensor MRU is installed on the ship deck below the rotation center of the pier to sense the roll, pitch and heave motion of the ship.

[0025] In summary, the present invention has the following beneficial effects:

[0026] The present invention uses an inertial sensor IMU, a GPS positioning system, and a laser radar in combination with a Kalman filter positioning algorithm, and utilizes multi-sensor fusion positioning to effectively overcome the system error caused by single sensor positioning. The Kalman filter is used to complement the determination of each sensor, and ultimately the precise positioning of the ship is achieved, thereby improving the accuracy of pier wave compensation. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] Figure 1 It is a flow chart of a pier active wave compensation method based on multi-sensor fusion positioning;

[0028] Figure 2 It is a structural schematic diagram of a pier in an active wave compensation method for a pier based on multi-sensor fusion positioning;

[0029] Figure 3 The present invention is a schematic diagram of various position points on a pier in an active wave compensation method for a pier based on multi-sensor fusion positioning.

[0030] In the figure, 1. trestle; 2. attitude sensor MRU; 3. inertial sensor IMU; 4. GPS positioning system; 5. laser radar; 6. redundant controller; 7. slewing joint rotary encoder; 8. variable amplitude joint displacement sensor; 9. telescopic joint rotary encoder. DETAILED DESCRIPTION

[0031] The present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0032] An active wave compensation method for pier based on multi-sensor fusion positioning, such as Figure 1 As shown, the specific steps include:

[0033] S1. By collecting ship data from laser radar 5, inertial sensor IMU 3, and GPS positioning system 4, the ship data is processed using improved Kalman filtering to achieve accurate positioning of the ship at sea. Figure 2 As shown, the inertial sensor IMU 3 is installed on the ship deck to sense the acceleration, tilt, impact, vibration, rotation and multi-degree-of-freedom motion of the ship; the GPS positioning system 4 is installed on the ship deck to accurately locate the position of the ship; the laser radar 5 is set at the end of the pier 1 to sense the positional relationship between the end of the pier 1 and the target connection object.

[0034] Specifically, the position information of the ship traveling at sea is collected by the laser radar 5, the inertial sensor IMU3 and the GPS positioning system 4. The output of the inertial sensor IMU3 is corrected by the filter through the indirect filtering method of filter output correction. The position and speed errors output by the inertial sensor IMU3 are used as the state vector of the loose combination system. The difference of the tag position calculated by the GPS positioning system 4, the laser radar 5 and the inertial sensor IMU3 is used as the measurement variable and input into the filter. Based on this, the discrete state space expression of the loose combination positioning system is established as follows: k =FX k-1 +W k-1 , Z k =HX k +V k , where X k and Z kare the system state variables and test variables at time k, F and H are the system state transfer matrix and system matrix respectively, W k-1 is the system process noise at time k-1, assuming its covariance is Q k , V k is the measurement noise at time k, assuming its covariance is R k .

[0035]

[0036] Among them, δP x ,δP y ,δP z They represent the position errors of the carrier on the X, Y, and Z axes respectively calculated by the inertial sensor IMU3, δυ x ,δυ y ,δυ z They represent the velocity errors of the carrier on the X, Y, and Z axes respectively calculated by the inertial sensor IMU3; T is the sampling time interval, Indicates the position of the carrier in the X, Y, and Z axis directions calculated by the inertial sensor IMU3. It indicates the position of the carrier in the X, Y and Z axis directions calculated by the GPS positioning system 4. It indicates that the laser radar 5 calculates the position of the carrier in the X, Y and Z axis directions.

[0037] Covariance of system process noise Where Q Px , Q Py , Q Pz are the covariance of the position error of the carrier on the x, y, and z axes respectively calculated by the inertial sensor IMU3, Q υx , Q υy , Q υz The covariance of the velocity error of the carrier on the x, y, and z axes is calculated by the inertial sensor IMU3. In The covariance of the measurement noise is

[0038] Assuming that both process noise and system noise are white noise, the KF method can be used to estimate the positioning error. 0 , initial value of covariance matrix P 0 According to the KF algorithm, the optimal estimated value of the positioning error at each sampling time can be estimated. The KF equation is as follows: The state one-step prediction is The covariance one-step forecast is P k|k-1 =FP k-1|k-1 F T +Qk , the filter gain is K k =P k|k-1 H T (HP k|k-1 H T +R k ) -1 , the final sensor state estimate is The ship position can be obtained and the covariance is updated to P k+1|k+1 =P k|k-1 -K k HP k|k-1 ; Among them, k|k-1 represents the value of point k-1 at time k, k-1|k-1 represents the value of point k-1 at time k-1, k|k represents the value of point k at time k, and k+1|k+1 represents the value of point k+1 at time k+1.

[0039] S2. Establish a coordinate system, taking the state when the ship is connected to the wind turbine tower at the end of the pier 1 under still water as the initial state, and establishing a rectangular coordinate system O with the rotation center of the ship at this time as the origin. Specifically, Figure 3 As shown, the Kalman filter is used to calculate The position of the ship is obtained, and the position of the fixed object target point C of the wind turbine tower, the position of the end position of the pier 1, the position of the rotation center of the pier 1, and the positions of the variable amplitude joint connection points D and E of the pier 1 are obtained through the pier 1 structure; the coordinate system is established with the center of gravity of the ship in the initial state as the coordinate origin O(0, 0, 0), and the coordinate conversion between the ship position and point O calculated by Kalman filtering is obtained to obtain the coordinate positions of points A, B, C, D and E in the O coordinate system, and the position of the fixed object target point C of the wind turbine tower in the initial state coincides with the position of the end position of the pier 1, point A; wherein, the coordinates of the fixed object target point C of the wind turbine tower of the pier 1 are (C x , C y , C z ), the coordinates of point A at the end of trestle 1 are (A x , A y , A z ), the coordinates of point B, the center of rotation of trestle bridge 1, are (B x , B y , B z ), the coordinates of point D and point E at the connection position of the trestle 1 variable amplitude joint are (D x , D y , D z ) and (E x , E y , E z ).

[0040] S3, the instantaneous sway, sway, pitch, roll, pitch and heave information of the ship obtained by the attitude sensor MRU2, and the motion attitude inverse calculation of the target position of each joint of the pier 1, including the extension amount S of the telescopic joint, the rotation amount R of the slewing joint and the extension amount L of the variable amplitude joint. Figure 2 As shown, the attitude sensor MRU2 is installed on the ship deck below the rotation center of the pier 1 to sense the roll, pitch and heave motion of the ship.

[0041] Specifically, the MRU attitude sensor measures the angular changes (x1, y1, z1) of the sway, pitch and pitch of the pier 1 on the x, y and z axes, and the displacement changes (x2, y2, z2) on the x, y and z axes, and obtains the rotation matrix M and translation matrix T of the pier 1 movement, where:

[0042] According to the rotation matrix M and the translation matrix T, the coordinates of the end position A' of the pier 1 and the rotation center position B' of the pier 1 after the wave movement can be obtained, where the coordinates of point A' are (A' x , A' y , A' z ), the coordinates of point B' are (B' x , B' y , B' z ),but

[0043] The coordinates of the end position A' of the pier 1 after the wave movement and the coordinates of the rotation center position B' can be used to obtain the expansion amount S required for active wave compensation of the pier 1, the rotation amount R of the slewing joint and the expansion amount L of the variable amplitude cylinder, where:

[0044] And I = GN × p, where G = [(D x -B x ) 2 +(D y -B y ) 2 +(D z -B z ) 2 ]+[(E x -B x ) 2 +(E y -B y ) 2 +(E z -B z ) 2 ],N=2[(D x -B x )×(E x -Bx )+(D y -B y )×(E y -B y )+(D z -B z )×(E z -B z )],

[0045] S4, control each joint to move smoothly to the target position to complete wave compensation. Figure 2 As shown, the variable amplitude joint displacement sensor 8 installed on the variable amplitude cylinder can measure the variable amplitude joint displacement, the swivel joint rotary encoder 7 installed on the swivel joint can measure the swivel joint angle, and the telescopic joint rotary encoder 9 installed on the telescopic joint can measure the telescopic joint displacement. The variable amplitude joint displacement sensor 8, the swivel joint rotary encoder 7, and the telescopic joint rotary encoder 9 can be used to detect whether the active wave compensation of the corresponding joint is in place, and the accuracy of the active wave compensation can be judged. If the accuracy of the active wave compensation exceeds the set range, the redundant controller 6 will control the switch to manual wave compensation mode.

[0046] The above description shows and describes the preferred embodiments of the present invention. As mentioned above, it should be understood that the present invention is not limited to the form disclosed herein, and should not be regarded as excluding other embodiments, but can be used in various other combinations, modifications and environments, and can be modified within the scope of the invention concept described herein through the above teachings or the technology or knowledge of the relevant field. The changes and modifications made by those skilled in the art do not depart from the spirit and scope of the present invention, and should be within the scope of protection of the claims attached to the present invention.

Claims

1. A method for active wave compensation of a pier based on multi-sensor fusion positioning, characterized in that: The specific steps include: S1, by collecting ship data from laser radar (5), inertial sensor IMU (3), and GPS positioning system (4), using improved Kalman filter to process the ship data, accurate positioning of the ship at sea is achieved; S2, establish a coordinate system, take the state when the ship is connected to the wind turbine tower at the end of the still water trestle (1) as the initial state, and establish a rectangular coordinate system O with the rotation center of the ship at this time as the origin; S3, the instantaneous sway, surge, pitch, roll, pitch and heave information of the ship is obtained by the attitude sensor MRU (2), and the motion attitude is inversely solved to calculate the target position of each joint of the pier (1), including the extension amount S of the telescopic joint, the rotation amount R of the slewing joint and the extension amount L of the luffing joint; S4, control each joint to move smoothly to the target position to complete wave compensation; In step S1, the position information of the ship traveling at sea is collected by the laser radar (5), the inertial sensor IMU (3) and the GPS positioning system (4), and the output of the inertial sensor IMU (3) is corrected by the filter through an indirect filtering method of filter output correction, and the position and speed errors output by the inertial sensor IMU (3) are used as the state vector of the loose combination system, and the difference of the tag position calculated by the GPS positioning system (4), the laser radar (5) and the inertial sensor IMU (3) is used as the measurement variable and input into the filter, and the discrete state space expression of the loose combination positioning system is established based on this: X k =FX k-1 +W k-1 Z k =HX k +V k Where X k and Z k are the system state variables and test variables at time k, , F and H are the state transfer matrix and system matrix of the system respectively, W k-1 is the system process noise at time k-1, assuming its covariance is Q k , V k is the measurement noise at time k, assuming its covariance is R k .

2. The method for active heave compensation of a pier based on multi-sensor fusion positioning according to claim 1, characterized in that: In the step S1, Among them, δP x ,δP y ,δP z They represent the position errors of the carrier on the X, Y, and Z axes respectively calculated by the inertial sensor IMU (3), δυ x ,δυ y ,δυ z They represent the velocity errors of the carrier on the X, Y, and Z axes respectively calculated by the inertial sensor IMU (3); T is the sampling time interval, Indicates the position of the carrier in the X, Y, and Z axis directions calculated by the inertial sensor IMU (3). It represents the position of the carrier in the X, Y and Z axis directions calculated by the GPS positioning system (4). It indicates the position of the carrier in the X, Y and Z axis directions calculated by the laser radar (5).

3. The method for active wave compensation of a pier based on multi-sensor fusion positioning according to claim 2 is characterized by: In step S1, given the initial state value X0 and the initial covariance matrix value P0, the optimal estimated value of the positioning error at each sampling time can be estimated according to the KF algorithm. The KF equation is as follows: The state one-step prediction is The covariance one-step forecast is P k|k-1 =FP k-1|k-1 F T +Q k , the filter gain is K k =P k|k-1 H T (HP k|k-1 H T +R k ) -1 , and the final sensor state estimate is The ship position can be obtained and the covariance is updated to P k+1|k+1 =P k|k-1 -K k HP k|k-1 ; Among them, k|k-1 represents the value of point k-1 at time k, k-1|k-1 represents the value of point k-1 at time k-1, k|k represents the value of point k at time k, and k+1|k+1 represents the value of point k+1 at time k+1.

4. The method for active heave compensation of a pier based on multi-sensor fusion positioning according to claim 3 is characterized by: In the step S1, Where Q Px , Q Py , Q Pz are the covariance of the position error of the carrier on the x, y, and z axes respectively calculated by the inertial sensor IMU (3), υx , Q υy , Q υz The inertial sensor IMU (3) is used to calculate the covariance of the velocity error of the carrier on the x, y, and z axes respectively.

5. The method for active wave compensation of a pier based on multi-sensor fusion positioning according to claim 4 is characterized by: In step S1, In but 6. The method for active heave compensation of a pier based on multi-sensor fusion positioning according to claim 5 is characterized by: In step S2, the Kalman filter is used to calculate The position of the ship is obtained, and the position of the fixed object target point C of the wind turbine tower, the position of the end position point A of the trestle (1), the position of the rotation center point B of the trestle (1), and the positions of the variable amplitude joint connection points D and E of the trestle (1) are obtained through the trestle (1) structure; a coordinate system is established with the center of gravity of the ship in the initial state as the coordinate origin O(0,0,0), and the coordinate conversion between the ship position and point O calculated by Kalman filtering is obtained to obtain the coordinate positions of point A, point B, point C, point D and point E in the O coordinate system, and the position of the fixed object target point C of the wind turbine tower in the initial state coincides with the position of the end position point A of the trestle (1); wherein the coordinate of the fixed object target point C of the wind turbine tower of the trestle (1) is (C x , C y , C z ), the coordinates of point A at the end of the trestle (1) are (A x , A y , A z ), the coordinates of point B, the rotation center of the trestle (1), are (B x , B y , B z ), the coordinates of point D and point E of the variable amplitude joint connection position of the trestle (1) are (D x , D y , D z ) and (E x , E y , E z ).

7. The method for active heave compensation of a pier based on multi-sensor fusion positioning according to claim 6, characterized in that: In step S3, the angular changes (x1, y1, z1) of the sway, pitch and pitch of the trestle (1) on the x, y and z axes and the displacement changes (x2, y2, z2) on the x, y and z axes are measured by the MRU attitude sensor to obtain the rotation matrix M and translation matrix T of the movement of the trestle (1), wherein:

8. The method for active heave compensation of a pier based on multi-sensor fusion positioning according to claim 7 is characterized by: In step S3, the coordinates of the end position A' of the pier (1) after the wave movement and the rotation center position B' of the pier (1) can be obtained according to the rotation matrix M and the translation matrix T, wherein the coordinates of the A' point are (A' x , A' y , A' z ), the coordinates of point B' are (B' x , B' y , B' z ),but 9. The method for active heave compensation of a pier based on multi-sensor fusion positioning according to claim 8, characterized in that: In step S3, the extension amount S required for active wave compensation of the pier (1), the rotation amount R of the slewing joint and the extension amount L of the variable amplitude cylinder can be obtained through the coordinates of the end position A' of the pier (1) after the wave movement and the coordinates of the rotation center position B'. And I = GN × p, where, 10. The method for active heave compensation of a pier based on multi-sensor fusion positioning according to claim 1, characterized in that: In the step S1, the inertial sensor IMU (3) is installed on the ship deck to sense the acceleration, tilt, impact, vibration, rotation and multi-degree-of-freedom motion of the ship; the GPS positioning system (4) is installed on the ship deck to accurately locate the position of the ship; the laser radar (5) is arranged at the end of the pier (1) to sense the positional relationship between the end of the pier (1) and the target connection object; in the step S3, the attitude sensor MRU (2) is installed on the ship deck below the rotation center of the pier (1) to sense the roll, pitch and heave motion of the ship.

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