Leveling system and leveling method for offshore operation platform

Abstract

The invention relates to the technical field of hydraulic engineering, in particular to an offshore operation platform leveling system which comprises an offshore platform, a plurality of supporting rods, a plurality of lifting devices, a plurality of speed measuring devices, a plurality of force sensors, a tilt angle sensor and a controller. The lifting devices are installed at the bottoms of the supporting rods in a one-to-one correspondence mode, the speed measuring sensors are installed on the offshore platform and correspond to the lifting devices in a one-to-one correspondence mode, each lifting device comprises a plurality of lifters and a plurality of stroke sensors, the lifters are installed on the supporting rods in a one-to-one correspondence mode, and the stroke sensors are installed on the lifters in a one-to-one correspondence mode. The stroke sensors are fixed to the side faces of the lifters in a one-to-one correspondence mode. The technical problem that rapid and accurate leveling of the offshore operation platform cannot be achieved through a leveling method in the prior art is solved, and it can be guaranteed that all the supporting rods can touch the ground by detecting the stress values of the rods in real time through the force sensors.

Description

Technical Field

[0001] This invention relates to the field of water conservancy engineering technology, specifically to a leveling system and method for offshore operation platforms. Background Technology

[0002] Existing offshore lifting platforms use manual leveling technology. During lifting operations, if the platform's tilt angle exceeds the limit, an over-limit alarm is triggered, and operators immediately stop the lifting operation. The system then switches to single-pile lifting mode, lifting only the leg that is moving too slowly during the lifting process. Once the platform's tilt angle is adjusted to the allowable range, manual leveling is completed. The system then switches to multi-pile coordinated lifting mode to continue lifting operations. This repeated leveling during the entire lifting process is too time-consuming, reducing the overall efficiency of the lifting platform. Manual leveling requires operators to first adjust the level based on the tilt angle value, which demands high operator skill and is not very practical. Furthermore, relying solely on the tilt angle signal can easily lead to misjudgments.

[0003] Chinese utility model patent CN113389995A, entitled "Platform Leveling System and Method," describes a method for leveling a three-legged platform. It uses tilt sensors to detect the platform's lateral and longitudinal tilt angles. Based on a preset relationship between tilt angle and elongation, it determines the first elongation of the first leg and the second elongation of the second leg, corresponding to both the lateral and longitudinal tilt angles. This determines the first leg at the platform's lowest point and the second leg at the platform's midpoint. Next, an adjuster determines the elongation of the first and second legs based on the tilt angle and elongation relationship. Finally, the adjuster completes the elongation of the first and second legs, thus leveling the platform. However, this patent only levels the three-legged platform, and each leveling process only adjusts the elongation of the first and second legs, not all legs. This makes the leveling process too slow and hinders rapid platform leveling.

[0004] Chinese utility model patent CN201910163653, entitled "An Automatic Leveling System and Method for Offshore Elevating Platforms," ​​uses data from two sensors to determine platform tilt. One sensor uses tilt angle data; when the tilt angle exceeds a limit, the platform enters automatic leveling mode and activates a PID-based automatic leveling module to level itself. The other sensor uses displacement data; when the difference between the maximum and minimum relative displacements of the legs exceeds a pre-set leveling threshold, the platform enters automatic leveling mode and activates the PID-based automatic leveling module. However, this patent lacks a force sensor to measure the ground contact force on each support rod. Therefore, this method cannot guarantee that all rods will be in contact with the ground after platform leveling. Furthermore, this method uses the difference between the maximum and minimum actual relative displacement of the pile legs as the starting signal for adjusting the platform. However, in the actual complex seabed, due to the complex topography, the length of each pole will be different after the platform is leveled. Therefore, the difference between the maximum and minimum actual relative displacement of the pile legs as the starting signal for adjusting the platform cannot be used. This method is only applicable to relatively flat terrain.

[0005] Chinese utility model patent CN113547493A, entitled "Automatic Leveling Method for Working Platforms," ​​describes a method that, when any point on the platform is subjected to external force, detects the voltage value generated by the piezoelectric ceramic sensor located in the self-sensing piezoelectric ceramic module, calculates the pressure on the drivable outriggers, and compares the pressures on different drivable outriggers to formulate a leveling control strategy. However, this method is not suitable for leveling offshore working platforms. Offshore working platforms are subject to heavy loads and are also affected by the constantly changing impact and buoyancy of seawater, resulting in varying piezoelectric values. This causes the different drivable outriggers on the platform to continuously extend and retract, making it impossible to complete the leveling task. Therefore, the piezoelectric detection method cannot be used for leveling offshore working platforms.

[0006] In summary, there is an urgent need for a leveling system and method that is applicable to various seabed terrains, can determine whether the support rod is in contact with the ground, and can quickly level the surface to solve the problems existing in the prior art. Summary of the Invention

[0007] The purpose of this invention is to provide a leveling system and method for offshore operating platforms, so as to solve the technical problem that existing leveling methods cannot achieve rapid and accurate leveling of offshore operating platforms. The specific technical solution is as follows:

[0008] This invention provides a leveling system for an offshore platform, comprising an offshore platform, multiple support rods, multiple lifting devices, multiple speed measuring devices, multiple force sensors, tilt sensors, and a controller. The support rods are spaced apart at the bottom of the offshore platform. Multiple lifting devices are installed one-to-one with the bottom of each support rod. Multiple speed measuring sensors are installed on the offshore platform and correspond one-to-one with each lifting device. Each lifting device includes multiple elevators and multiple travel sensors. Each elevator is installed one-to-one with each support rod, and each travel sensor is fixed to the side of each elevator. The controller is connected to the multiple elevators, multiple travel sensors, multiple speed measuring devices, multiple force sensors, and tilt sensors. The tilt sensors are located at the center of the offshore platform.

[0009] The present invention also provides a leveling method using the leveling system of the offshore operation platform as described above, comprising the following steps: establishing a rectangular coordinate system on the horizontal plane of the offshore operation platform, and obtaining the coordinate position of each support rod of the offshore operation platform on the rectangular coordinate system, wherein the coordinate position includes coordinate values ​​in the three directions of X, Y and Z axes;

[0010] All support rods are extended, and the ground force value of each support rod is measured in real time using force sensors to ensure that all support rods are in contact with the ground.

[0011] The tilt sensor measures the rotation angle of the offshore platform in the X and Y axes in real time. The measured rotation angle is then substituted into the Euler angle calculation formula for the rotation angle around the X and Y axes to calculate the target coordinate value of each support rod on the Z axis.

[0012] The elongation of each support rod was calculated using the height-tracking method.

[0013] The position data of all support rods is measured by stroke sensors, the force data of all support rods is measured by force sensors, and the extension and retraction speed of all support rods is measured by speed measuring devices. The stability and extension of all support rods on the platform are achieved by using an adaptive unscented Kalman filter algorithm and a force-position hybrid fuzzy PID control algorithm.

[0014] Once all support rods have extended to their full length, the tilt angle of the offshore platform is continuously monitored using tilt sensors. If the detected tilt angle value does not meet the set minimum tilt angle value range, the above leveling process is repeated until the tilt angle value of the offshore platform meets the set minimum tilt angle value range, at which point the leveling of the offshore platform is complete.

[0015] A further improvement of the offshore platform leveling method of the present invention is that, when the ground force value of all support rods is measured in real time by force sensors, if the value detected by the force sensors is less than the target ground force value of the support rod, the support rod continues to be extended; if the value detected by the force sensors is greater than the target ground force value, the extension of the support rod is stopped.

[0016] A further improvement of the leveling method for offshore operating platforms in this invention lies in the fact that, when substituting the measured value of the rotation angle into the calculation formulas for the rotation angles around the X-axis and Y-axis in Euler angles:

[0017] Substitute the tilt angle values ​​of the X and Y axes of the offshore platform into the Euler angle calculation formula 1) for the rotation angles around the X and Y axes to calculate the target coordinate values ​​of each support rod on the Z axis:

[0018]

[0019] Where (x0,y0,z0) are the calculated actual coordinate positions of each support rod of the offshore platform, β is the angle value of the offshore platform rotating around the X-axis, α is the angle value of the offshore platform rotating around the Y-axis, (x1,y1,z1) are the coordinate positions of each support rod when the offshore platform is in a horizontal position, and T is the sign of the matrix transpose.

[0020] A further improvement of the offshore platform leveling method of the present invention is that, when calculating the elongation of each support rod using the height-tracking method, the longest elongated rod length among all support rods is determined, and the target elongation of each support rod is calculated using the height-tracking method to determine the target position of each support rod after elongation.

[0021] A further improvement to the offshore platform leveling method of this invention lies in the following calculation formula for the adaptive unscented Kalman filter algorithm:

[0022] State prediction:

[0023] x k+1 =f(x) k ,u k ) 2); Where, x k+1 It is the predicted value at time k+1, f is the system's state transition function, and x is the predicted value. k It is the predicted value at time k, u k It is the system control input at time k;

[0024] Covariance prediction:

[0025]

[0026] Among them, P k+1 Let A be the covariance matrix at time k+1.k P is the state transition matrix at time k. k Q is the covariance matrix at time k. k It is the process noise covariance matrix at time k;

[0027] Measurement and prediction:

[0028] z k+1 =h(x k+1 ) 4);

[0029] Among them, z k+1 is the predicted measurement value at time k+1, and h is the observation function;

[0030] Calculate the residuals:

[0031] z″ k+1 =z′ k+1 -z k+1 5);

[0032] Among them, z' k+1 It is the measurement value at time k+1, z” k+1 It is the residual of the state estimate at time k+1;

[0033] Measurement residual covariance:

[0034]

[0035] Among them, S k+1 H is the measurement residual covariance matrix at time k+1. k+1 It is the observation matrix at time k+1, R k+1 It is the observation noise covariance matrix at time k+1;

[0036] Calculate the Kalman gain:

[0037]

[0038] Among them, K k+1 It is the Kalman gain at time k+1;

[0039] Updated state estimate:

[0040] x k+1 =x k+1 +K k+1 z″ k+1 8);

[0041] Update the covariance matrix:

[0042] P k+1 =P k+1 -K k+1 H k+1 P k+19);

[0043] Update process noise covariance matrix:

[0044]

[0045] Among them, Q k+1 It is the process noise covariance matrix at time k+1; Q k It is the process noise covariance matrix at time k; α k These are the adaptive coefficients at time k;

[0046] Update the observation noise covariance matrix:

[0047]

[0048] Among them, R k β is the observation noise covariance matrix at time k; k These are the adaptive coefficients at time k;

[0049] The position data, force data, and extension / retraction speed data of all current support rods are obtained by calculating using formulas 1) to 11).

[0050] A further improvement to the offshore platform leveling method of this invention lies in adjusting the K value of the force-position hybrid fuzzy PID control algorithm before calculation. ep K ei K ed K fp K fi K fd The control parameters are calculated using the following formula:

[0051]

[0052] Among them, K ep It is the position proportional gain, K ei It is the position integral gain, K ed It is the position differential gain, K fp It is force proportional gain, K fi It is the force integral gain, K fd It is the force differential gain, a ep c ep It is K ep Regarding the coefficient value for the change in rod length, a ei c ei It is K ei Regarding the coefficient value for the change in rod length, a ed c ed It is K ed Regarding the coefficient value for the change in rod length, a fp c fpIt is K fp Regarding the coefficient value for the change in rod length, a fi c fi It is K fi Regarding the coefficient value for the change in rod length, a fd c fd It is K fd Regarding the coefficient value of the change in rod length, d ep It is K ep The adjustment constant, d ei It is K ei The adjustment constant, d ed It is K ed The adjustment constant, d fp It is K fp The adjustment constant, d fi It is K fi The adjustment constant, d fd It is K fd The adjustment constant is ΔL, where ΔL is the elongation of the support rod and ΔF is the change in force on the support rod. i It is the target length value of each support rod, L' i This refers to the real-time extension position of each support rod, F. i F' is the specified ground contact value for each support rod. i is the real-time ground contact value of each support rod, and n is the total number of support rods.

[0053] A further improvement to the leveling method for offshore operating platforms in this invention lies in the force-position hybrid fuzzy PID calculation formula:

[0054]

[0055] Where e(t) is the positional deviation, u p (t) is the output of position control, d(t) is the time derivative of this formula, g(t) is the force deviation, and u f (t) is the output of force control, α1 is the adjustment coefficient of position control output, β1 is the adjustment coefficient of force control output, and r p r is the adjustment coefficient for the change in rod position. f It is the adjustment coefficient for the change in force on the rod, u(t) is the final output control signal, and ΔF is the control signal. f Both ΔF and ΔL represent the change in force on the support rod. p Both ΔL and ΔL represent the elongation of the support rod, de(t) is the derivative of the position deviation function, dt is the derivative of the time period of each execution of the formula, dg(t) is the derivative of the force deviation function, and threadF is the defined minimum threshold for the change in force on the support rod.

[0056] The application of the technical solution of the present invention has the following beneficial effects:

[0057] This invention relates to a leveling system for offshore platforms. Based on an adaptive unscented Kalman filter algorithm and a force-position hybrid fuzzy PID control algorithm, it achieves rapid and stable extension and retraction control of each support rod of the offshore platform, solving the technical problem that existing leveling methods cannot achieve rapid and accurate leveling of offshore platforms. This invention can level offshore platforms with two or more support rods, and the use of force sensors to detect the force values ​​on the rods in real time ensures that all support rods are in contact with the ground.

[0058] In addition to the objectives, features, and advantages described above, the present invention has other objectives, features, and advantages. The invention will now be described in further detail with reference to the figures. Attached Figure Description

[0059] The accompanying drawings, which form part of this application, are used to provide a further understanding of the invention. The illustrative embodiments of the invention and their descriptions are used to explain the invention and do not constitute an undue limitation of the invention. In the drawings:

[0060] Figure 1 This is a schematic diagram of the structure of the offshore platform leveling system of the present invention. Figure 1 ;

[0061] Figure 2 This is a schematic diagram of the structure of the offshore platform leveling system of the present invention. Figure 2 ;

[0062] Figure 3 This is a flowchart of the force-position hybrid fuzzy PID control algorithm based on adaptive unscented Kalman filtering for the leveling method of offshore operation platforms of the present invention;

[0063] Figure 4 This is a flowchart of the leveling algorithm for the offshore platform leveling method of the present invention;

[0064] Figure 5 It is a graph showing the results of noise signal processing by the PID algorithm in the existing technology;

[0065] Figure 6 It is a graph showing the results of noise signal processing using the fuzzy PID algorithm in the existing technology;

[0066] Figure 7 This is a graph showing the noise signal processing results of the force-position hybrid fuzzy PID control algorithm based on adaptive unscented Kalman filtering for the leveling method of the offshore operation platform of this invention.

[0067] Among them, 1. offshore operation platform; 2. controller; 3. tilt sensor; 4. lifting device; 5. speed measuring device; 6. elevator; 7. stroke sensor; 8. force sensor. Detailed Implementation

[0068] The embodiments of the present invention will be described in detail below with reference to the accompanying drawings.

[0069] See Figures 1 to 7 As shown, a leveling system for an offshore platform 1 includes an offshore platform, multiple support rods, multiple lifting devices 4, multiple speed measuring devices 5, multiple force sensors 8, tilt sensors 3, and a controller 2. The support rods are spaced apart at the bottom of the offshore platform. Each lifting device 4 is correspondingly installed at the bottom of each support rod. Multiple speed measuring sensors are installed on the offshore platform and correspond to each lifting device 4. Each lifting device 4 includes multiple elevators 6 and multiple travel sensors 7. Each elevator 6 is correspondingly installed on one of the support rods, and each travel sensor is correspondingly fixed to the side of each elevator 6. The controller 2 is connected to the multiple elevators 6, multiple travel sensors 7, multiple speed measuring devices 5, multiple force sensors 8, and tilt sensors 3. The tilt sensors 3 are located at the center of the offshore platform.

[0070] The controller 2 is connected via communication to multiple elevators 6, multiple stroke sensors 7, multiple speed measuring devices 5, multiple force sensors 8, and tilt sensors 3. It calculates and processes the detection data from tilt sensors 3, speed measuring devices 5, stroke sensors 7, and force sensors 8, and controls the forward, reverse, and stopping rotation of elevators 6. The lifting device 4 is the mechanical structure that enables the extension and retraction of the support rods of the offshore platform. Elevators 6 provide the power for the lifting device 4. Speed ​​measuring devices 5 measure the lifting speed of elevators 6, serving as the data basis for the control algorithm to control the extension and retraction of the support rods. Tilt sensors 3 detect the rotation angle of the offshore platform 1 on the X and Y axes. Stroke sensors 7 measure the extension value of each support rod of the offshore platform 1. Force sensors 8 are installed at the bottom of each support rod on the offshore platform to detect the ground force value of all support rods, ensuring that all support rods are in contact with the ground. Regarding the determination of whether a support rod is in contact with the ground, the target ground contact value of the support rod in force sensor 8 needs to be determined based on the actual working conditions. The leveling system can calibrate the horizontal position of the offshore operation platform 1, and use the tilt sensor 3 to determine the angle detection benchmark of the offshore operation platform 1 in the X and Y axis directions.

[0071] This leveling system can level platforms with two or more support rods. It employs a proposed force-position hybrid fuzzy PID (Process Identifier) ​​control algorithm based on adaptive unscented Kalman filtering to simultaneously adjust the extension and retraction of each rod, enabling rapid and stable leveling of the offshore platform 1. Force sensors 8 detect the force values ​​on each support rod. If the detected value is less than the target ground contact value, the rod continues to extend; if the detected value is greater than the target ground contact value, the extension stops, indicating that the support rod is now on the ground. This method ensures that all support rods are on the ground after the platform is leveled. Using data from tilt sensors 3 as the basis for adjusting the platform's levelness, and employing force sensors 8 to detect the force on each support rod to ensure all support rods are on the ground, the leveling method of this invention is well-suited for leveling offshore platform 1.

[0072] The present invention also provides a leveling method using the leveling system of the offshore operation platform 1 as described above, comprising the following steps: establishing a rectangular coordinate system on the horizontal plane of the offshore operation platform 1, obtaining the coordinate position of each support rod of the offshore operation platform 1 on the rectangular coordinate system, the coordinate position including the coordinate values ​​in the three directions of X, Y and Z axes;

[0073] All support rods are extended, and the ground force value of all support rods is measured in real time by force sensor 8 to ensure that all support rods are in contact with the ground.

[0074] The tilt sensor 3 measures the rotation angle of the offshore operation platform 1 in the X and Y axes in real time. The measured value of the rotation angle is substituted into the Euler angle calculation formula for the rotation angle around the X and Y axes to calculate the target coordinate value of each support rod on the Z axis.

[0075] The elongation of each support rod was calculated using the height-tracking method.

[0076] The position data of all support rods is measured by stroke sensor 7, the force data of all support rods is measured by force sensor 8, and the extension and retraction speed of all support rods is measured by speed measuring device 5. The stability and extension of all support rods on the platform are achieved by using an adaptive unscented Kalman filter algorithm and a force-position hybrid fuzzy PID control algorithm.

[0077] Once all support rods have extended to their full length, the tilt angle of the offshore work platform 1 is continuously detected by the tilt sensor 3. If the detected tilt angle value does not reach the set minimum tilt angle value range, the above leveling process is repeated on the offshore work platform 1 until the tilt angle value of the offshore work platform 1 meets the set minimum tilt angle value range, and the leveling of the offshore work platform 1 is completed.

[0078] Figure 4 The flowchart for the leveling algorithm is as follows: First, the pressure values ​​of each support rod are obtained through force sensor 8. It is then determined whether the pressure values ​​of each support rod are greater than the minimum ground contact value. If not, fuzzy PID speed regulation is used to extend the support rods that do not meet the condition, while not extending the support rods that do meet the condition. The process then returns to obtaining the pressure values ​​of each support rod through force sensor 8. If the pressure values ​​are greater than the minimum ground contact value, the platform angle is checked. If the angle values ​​meet the minimum range, the leveling process ends. If not, the extension of each support rod is calculated based on the detected x and y axis angle values. Based on the extension, the platform is leveled using a height-tracking method. A force-position hybrid fuzzy PID control algorithm based on adaptive unscented Kalman filtering is used to control the extension of each support rod. The algorithm then determines the extension of each support rod. If the struts have not fully extended, a force-position hybrid fuzzy PID control algorithm based on adaptive unscented Kalman filtering is used to control the struts that have not fully extended to continue extending to the full length. Then, the process returns to determine if each strut has fully extended. If so, the pressure values ​​of each strut are obtained through force sensor 8. It is then determined whether the pressure values ​​of each strut are greater than the minimum ground contact value. If not, fuzzy PID speed regulation is used to extend the struts that do not meet the conditions, while not extending the struts that do meet the conditions. The process returns to obtain the pressure values ​​of each strut through force sensor 8. If so, it is determined whether the platform angle values ​​meet the minimum range value. If not, the process returns to calculate the extension amount of each strut based on the detected x and y axis angle values. If so, the leveling process ends.

[0079] The specific leveling steps are as follows:

[0080] 1. The force sensor 8 measures the ground force of all support rods in real time. If the value detected by the force sensor 8 is less than the target ground force value of the support rod, the support rod will continue to be extended; if the value detected by the force sensor 8 is greater than the target ground force value of the support rod, the extension of the support rod will stop.

[0081] 2. Substitute the tilt angle values ​​of the X and Y axes of the offshore operating platform 1 into the Euler angle calculation formula 1) for the rotation angles around the X and Y axes to calculate the target coordinate values ​​of each support rod on the Z axis:

[0082]

[0083] Where (x0,y0,z0) are the calculated actual coordinate positions of each support rod of the offshore platform, β is the angle value of the offshore platform rotating around the X-axis, α is the angle value of the offshore platform rotating around the Y-axis, (x1,y1,z1) are the coordinate positions of each support rod when the offshore platform is in a horizontal position, and T is the sign of the matrix transpose.

[0084] Calculate the coordinate value of each rod on the Z-axis according to Formula 1), determine the longest rod length among all support rods, and calculate the target elongation of each support rod using the height-tracking method to determine the target position of each support rod after elongation.

[0085] The PID parameters, as well as the partial matrices, adjustment coefficients, and adjustment constants in the proposed force-position hybrid fuzzy PID control algorithm based on the adaptive unscented Kalman filter algorithm, need to be determined according to the actual working conditions.

[0086] The proposed force-position hybrid fuzzy PID control algorithm based on adaptive unscented Kalman filtering algorithm is used to process the position data of all support rods measured by stroke sensor 7, the force data of all support rods measured by force sensor 8, the elongation information of all support rods calculated above, the target ground value, and the extension and retraction speed information of all support rods measured by velocity measuring device 5.

[0087] An adaptive unscented Kalman filter algorithm is used to filter the position data of all support rods measured by stroke sensor 7, the force data of all support rods measured by force sensor 8, and the extension and retraction speed data of support rods measured by speed measuring device 5. In this process, the position data and extension and retraction speed data of support rods need to be fused to obtain more accurate position data and speed data of support rods.

[0088] The calculation formula for the adaptive unscented Kalman filter algorithm is as follows:

[0089] (1) State prediction:

[0090] x k+1 =f(x) k ,u k ) 2); where x k+1 It is the predicted value at time k+1, f is the system's state transition function, and x is the predicted value. k It is the predicted value at time k, u k It is the system control input at time k;

[0091] (2) Covariance prediction:

[0092]

[0093] Among them, Pk+1 Let A be the covariance matrix at time k+1. k P is the state transition matrix at time k. k Q is the covariance matrix at time k. k It is the process noise covariance matrix at time k;

[0094] (3) Measurement and prediction:

[0095] z k+1 =h(x k+1 ) 4);

[0096] Among them, z k+1 is the predicted measurement value at time k+1, and h is the observation function;

[0097] (4) Calculate the residuals:

[0098] z″ k+1 =z′ k+1 -z k+1 5);

[0099] Among them, z' k+1 It is the measurement value at time k+1, z” k+1 It is the residual of the state estimate at time k+1;

[0100] (5) Measuring residual covariance:

[0101]

[0102] Among them, S k+1 H is the measurement residual covariance matrix at time k+1. k+1 It is the observation matrix at time k+1, R k+1 It is the observation noise covariance matrix at time k+1;

[0103] (6) Calculate the Kalman gain:

[0104]

[0105] Among them, K k+1 It is the Kalman gain at time k+1;

[0106] (7) Update the state estimate:

[0107] x k+1 =x k+1 +K k+1 z″ k+1 8);

[0108] (8) Update the covariance matrix:

[0109] P k+1 =P k+1-K k+1 H k+1 P k+1 9);

[0110] (9) Update the process noise covariance matrix:

[0111]

[0112] Among them, Q k+1 It is the process noise covariance matrix at time k+1; Q k It is the process noise covariance matrix at time k; α k It is the adaptive coefficient at time k, used to adjust the adjustment rate of process noise;

[0113] (10) Update the observation noise covariance matrix

[0114]

[0115] Among them, R k β is the observation noise covariance matrix at time k; k It is the adaptive coefficient at time k, used to adjust the adjustment rate of the observation noise;

[0116] (11) Determination of fuzzy rules

[0117] The position data, force data, and extension / retraction speed data of all support rods are calculated using formulas 1) to 11). Then, using the extension amount and target ground contact value of the support rods, the K-axis of the force-position hybrid fuzzy PID controller is adjusted using the following formula. ep K ei K ed K fp K fi K fd The control parameters are calculated using the following formulas:

[0118]

[0119] Among them, K ep It is the position proportional gain, K ei It is the position integral gain, K ed It is the position differential gain, K fp It is force proportional gain, K fi It is the force integral gain, K fd It is the force differential gain, a ep c ep It is K ep Regarding the coefficient value for the change in rod length, a ei c ei It is K ei Regarding the coefficient value for the change in rod length, aed c ed It is K ed Regarding the coefficient value for the change in rod length, a fp c fp It is K fp Regarding the coefficient value for the change in rod length, a fi c fi It is K fi Regarding the coefficient value for the change in rod length, a fd c fd It is K fd Regarding the coefficient value of the change in rod length, d ep It is K ep The adjustment constant, d ei It is K ei The adjustment constant, d ed It is K ed The adjustment constant, d fp It is K fp The adjustment constant, d fi It is K fi The adjustment constant, d fd It is K fd The adjustment constant is ΔL, where ΔL is the elongation of the support rod and ΔF is the change in force on the support rod. i It is the target length value of each support rod, L' i This refers to the real-time extension position of each support rod, F. i F' is the specified ground contact value for each support rod. i These are the real-time ground contact values ​​of each support rod, and n is the total number of support rods. The values ​​of each of these parameters need to be determined based on the actual situation.

[0120] (12) Force-position hybrid fuzzy PID calculation formula:

[0121]

[0122] Where e(t) is the positional deviation, u p (t) is the output of position control, d(t) is the time derivative of this formula, g(t) is the force deviation, and u f (t) is the output of force control, α1 is the adjustment coefficient of position control output, β1 is the adjustment coefficient of force control output, and r p r is the adjustment coefficient for the change in rod position. f It is the adjustment coefficient for the change in force on the rod, u(t) is the final output control signal, and ΔF is the control signal. f Both ΔF and ΔL represent the change in force on the support rod. pBoth ΔL and ΔL represent the elongation of the support rod, de(t) is the derivative of the position deviation function, dt is the derivative of the time period of each execution of the formula, dg(t) is the derivative of the force deviation function, and threadF is the defined minimum threshold for the change in force on the support rod.

[0123] The output value of the force-position hybrid fuzzy PID controller 2 and the speed value of the support rod obtained by the adaptive unscented Kalman filter algorithm are simultaneously input into the fuzzy PID controller 2. Finally, the output value of the fuzzy PID controller 2 controls the extension speed of each support rod, thereby realizing the rapid extension and retraction adjustment of the support rod, so that all support rods on the offshore operation platform 1 are extended and retracted to the set support rod length position.

[0124] Figure 3 The flowchart shows the force-position hybrid fuzzy PID control algorithm based on adaptive unscented Kalman filtering. The specific operation process is as follows: the data measured by the speed measuring device 5 and the data measured by the stroke sensor 7 are used to calculate the speed data and position data of the support rod extension using the adaptive unscented Kalman filtering algorithm. The data measured by the force sensor 8 is then calculated using the adaptive unscented Kalman filtering algorithm and combined with the target ground value of the support rod for force-position hybrid fuzzy PID control calculation. The target position of the support rod extension and the position data of the support rod are then combined for force-position hybrid fuzzy PID control calculation. Finally, the speed data and the data calculated by force-position hybrid fuzzy PID control are combined for fuzzy PID calculation to obtain the extension and retraction speed of the support rod.

[0125] The existing curves of the processing results of noisy signals using the PID algorithm are as follows: Figure 5 As shown in the figure, the curves of the processing results of existing fuzzy PID algorithms for noisy signals are as follows: Figure 6 As shown in the figure, the curve of the force-position hybrid fuzzy PID control algorithm based on adaptive unscented Kalman filtering proposed in this application for processing noisy signals is as follows. Figure 7 As shown. Figure 5 , Figure 6 and Figure 7 The horizontal axis represents time, and the vertical axis represents response.

[0126] Third, tilt sensor 3 is required to monitor the rotation angle of offshore platform 1 in the X and Y axes in real time. If, after leveling, the rotation angle of offshore platform 1 in the X and Y axes is detected again and the rotation angle in one direction does not meet the set minimum range value, the leveling steps above need to be repeated until the rotation angle of offshore platform 1 in both the X and Y axes meets the set minimum range value, at which point the leveling of offshore platform 1 stops. The flowchart of the leveling algorithm is as follows. Figure 4 As shown.

[0127] This invention uses the Euler angle calculation formula and the height-tracking method to determine the elongation of each support rod. Then, it employs the proposed force-position hybrid fuzzy PID control algorithm based on adaptive unscented Kalman filtering to achieve rapid and stable extension and retraction of each support rod of the offshore operation platform 1 to a specified length. Force sensors 8 are used to determine whether each support rod is touching the ground. The elongation of each support rod of the offshore operation platform 1 is determined using the Euler angle calculation formula and the height-tracking method.

[0128] This invention relates to a leveling system for an offshore work platform 1. Based on an adaptive unscented Kalman filter algorithm and a force-position hybrid fuzzy PID control algorithm, it achieves rapid and stable extension and retraction control of each support rod of the offshore work platform 1, solving the technical problem that existing leveling methods cannot achieve rapid and accurate leveling of the offshore work platform 1. This invention can level offshore platforms with two or more support rods, and the use of force sensors 8 to detect the force values ​​on the rods in real time ensures that all support rods are in contact with the ground.

[0129] The above description is merely a preferred embodiment of the present invention and is not intended to limit the invention. Various modifications and variations can be made to the present invention by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. An offshore platform leveling system, characterized by, The application relates to a marine platform, a plurality of support rods, a plurality of lifting devices, a plurality of speed measuring devices, a plurality of force sensors, an inclination sensor and a controller, the plurality of support rods are installed at intervals on the bottom of the marine platform, the plurality of lifting devices are installed one by one on the bottom of each support rod, the plurality of speed measuring sensors are installed on the marine platform and correspond to the lifting devices one by one, the lifting device comprises a plurality of elevators and a plurality of stroke sensors, the elevators are installed one by one on the support rods, the stroke sensors are fixed one by one on the side of the elevators, the controller is connected to the plurality of elevators, the plurality of stroke sensors, the plurality of speed measuring devices, the plurality of force sensors and the inclination sensor, and the inclination sensor is located at the center of the marine platform.

2. A method of levelling using a levelling system for an offshore work platform according to claim 1, characterised in that The application comprises the following steps: A rectangular coordinate system is established on the horizontal plane of the marine operation platform to obtain the coordinate position of each support rod of the marine operation platform in the rectangular coordinate system, and the coordinate position comprises coordinate values in the X, Y and Z axes; All the support rods are elongated, and the force values of all the support rods are measured in real time through the force sensors to ensure that all the support rods are in the landing state; The rotation angle of the marine operation platform in the X and Y axes is measured in real time through the inclination sensor, the measured value of the rotation angle is substituted into the rotation angle calculation formula of the X and Y axes in the Euler angle, and the target coordinate value of each support rod in the Z axis is calculated; The elongation of each support rod is calculated by using the high pursuit method; The position data of all the support rods are measured through the stroke sensors, the force data information of all the support rods are measured through the force sensors, and the extension speed information of all the support rods is measured through the speed measuring device, and the stability and elongation of all the support rods on the platform are completed through the adaptive unscented Kalman filtering algorithm and the force-position hybrid fuzzy PID control algorithm; When all the support rods are elongated to the position, the inclination of the marine operation platform is detected through the inclination sensor, if the detected inclination value does not reach the set minimum inclination value range, the leveling process of the marine operation platform is repeatedly executed once again until the inclination value of the marine operation platform meets the set minimum inclination value range, and the leveling of the marine operation platform is completed.

3. The offshore platform leveling method of claim 2, wherein, When the force values of all the support rods are measured in real time through the force sensors, if the value detected by the force sensor is smaller than the target landing value of the support rod, the elongation of the support rod is continued; if the value detected by the force sensor is greater than the target landing value of the support rod, the elongation of the support rod is stopped.

4. The offshore platform leveling method of claim 2, wherein, When the measured value of the rotation angle is substituted into the rotation angle calculation formula of the X and Y axes in the Euler angle: The inclination values of the X and Y axes of the marine operation platform are substituted into the rotation angle calculation formula 1) of the X and Y axes in the Euler angle, and the target coordinate value of each support rod in the Z axis is calculated: Wherein, (x0, y0, z0) is the calculated actual coordinate position of each support rod of the offshore platform, β is the angle value of the offshore platform rotating around the X axis, α is the angle value of the offshore platform rotating around the Y axis, (x1, y1, z1) is the coordinate position of each support rod of the offshore platform when the offshore platform is in the horizontal position, and T is the symbol of matrix transposition.

5. The offshore platform leveling method of claim 2, wherein, In the use of the chasing high method, the longest rod length value of the elongation of all support rods is determined, and the target elongation of each support rod is calculated by the chasing high method to determine the target position of each support rod after elongation.

6. The offshore platform leveling method of claim 2, wherein, The calculation formula of the adaptive unscented Kalman filtering algorithm is as follows: State prediction: x k+1 = f(x k , u k ) 2) ; where x k+1 is the prediction value at time k + 1, f is the state transition function of the system, x k is the prediction value at time k; u k is the system control input at time k; Covariance prediction: where P k+1 is the covariance matrix at time k + 1, A k is the state transition matrix at time k, P k is the covariance matrix at time k, Q k is the process noise covariance matrix at time k; Measurement prediction: z k+1 = h(x k+1 ) 4) ; where z k+1 is the predicted measurement at time k + 1, and h is the observation function. Calculate the residual: z" k+1 = z' k+1 - z k+1 5); where z'k+1is the measurement value at k+1, z"k+1is the state estimation residual at k+1. k+1 k+1 is the measurement value at k+1, z"k+1is the state estimation residual at k+1.​ Measurement residual covariance: where S k+1 is the measurement residual covariance matrix at time k + 1, H k+1 is the observation matrix at time k + 1, and R k+1 is the observation noise covariance matrix at time k + 1. Calculate the Kalman gain: where K k+1 is the Kalman gain at time k + 1. Update the state estimate: x k+1 = x k+1 + K k+1 z" k+1 8); Update the covariance matrix: P k+1 = P k+1 - K k+1 H k+1 P k+1 9); Update the process noise covariance matrix: where Q k+1 is the process noise covariance matrix at time k + 1; Q k is the process noise covariance matrix at time k; a k is the adaptive coefficient at time k; Update the observation noise covariance matrix: where R k is the observation noise covariance matrix at time k; β k is the adaptive coefficient at time k; The position data, force data information and telescopic speed data of all support rods are calculated by formula 1) to formula 11).

7. The offshore platform leveling method of claim 6, wherein, Before calculating by the force-position hybrid fuzzy PID control algorithm, the control parameters of the force-position hybrid fuzzy PID are adjusted ep , K ei , K ed , K fp , K fi , K fd are calculated, and the calculation formula is as follows: Among them, K ep It is the position proportional gain, K ei It is the position integral gain, K ed It is the position differential gain, K fp It is force proportional gain, K fi It is the force integral gain, K fd It is the force differential gain, a ep c ep It is K ep Regarding the coefficient value for the change in rod length, a ei c ei It is K ei Regarding the coefficient value for the change in rod length, a ed c ed It is K ed Regarding the coefficient value for the change in rod length, a fp c fp It is K fp Regarding the coefficient value for the change in rod length, a fi c fi It is K fi Regarding the coefficient value for the change in rod length, a fd c fd It is K fd Regarding the coefficient value of the change in rod length, d ep It is K ep The adjustment constant, d ei It is K ei The adjustment constant, d ed It is K ed The adjustment constant, d fp It is K fp The adjustment constant, d fi It is K fi The adjustment constant, d fd It is K fd The adjustment constant is ΔL, where ΔL is the elongation of the support rod and ΔF is the change in force on the support rod. i It is the target length value of each support rod, L' i This refers to the real-time extension position of each support rod, F. i F' is the specified ground contact value for each support rod. i is the real-time ground contact value of each support rod, and n is the total number of support rods.

8. The offshore platform leveling method of claim 7, wherein, Force-position hybrid fuzzy PID calculation formula: where e(t) is a position deviation, u p (t) is an output of the position control, d(t) is a derivation of time for the formula, g(t) is a force deviation, u f (t) is an output of the force control, a1 is a regulation coefficient of the position control output, b1 is a regulation coefficient of the force control output, r p is a regulation coefficient of a change amount of the rod position, r f is a regulation coefficient of a change amount of the rod force, u(t) is a control signal of the final output, AF f and AF both represent a change amount of the rod force, AL p and AL both represent an elongation amount of the rod, de(t) is a derivation of the position deviation function, dt is a differential of a time period for each execution of the formula, dg(t) is a derivation of the force deviation function, and threadF represents a minimum threshold value defined for the change amount of the rod force.

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