EP2123588A1 - Commande de grue dotée d'une suite active de houle - Google Patents

Commande de grue dotée d'une suite active de houle Download PDF

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Publication number
EP2123588A1
EP2123588A1 EP09006080A EP09006080A EP2123588A1 EP 2123588 A1 EP2123588 A1 EP 2123588A1 EP 09006080 A EP09006080 A EP 09006080A EP 09006080 A EP09006080 A EP 09006080A EP 2123588 A1 EP2123588 A1 EP 2123588A1
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Prior art keywords
movement
crane
load
model
dft
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EP09006080A
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German (de)
English (en)
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EP2123588B1 (fr
Inventor
Klaus Dr. Schneider
Oliver Sawodny
Jörg Neupert
Tobias Mahl
Sebastian Küchler
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Liebherr Werk Nenzing GmbH
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Liebherr Werk Nenzing GmbH
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    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B66—HOISTING; LIFTING; HAULING
    • B66C—CRANES; LOAD-ENGAGING ELEMENTS OR DEVICES FOR CRANES, CAPSTANS, WINCHES, OR TACKLES
    • B66C13/00—Other constructional features or details
    • B66C13/04—Auxiliary devices for controlling movements of suspended loads, or preventing cable slack
    • B66C13/06—Auxiliary devices for controlling movements of suspended loads, or preventing cable slack for minimising or preventing longitudinal or transverse swinging of loads
    • B66C13/063—Auxiliary devices for controlling movements of suspended loads, or preventing cable slack for minimising or preventing longitudinal or transverse swinging of loads electrical
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B63—SHIPS OR OTHER WATERBORNE VESSELS; RELATED EQUIPMENT
    • B63B—SHIPS OR OTHER WATERBORNE VESSELS; EQUIPMENT FOR SHIPPING 
    • B63B27/00—Arrangement of ship-based loading or unloading equipment for cargo or passengers
    • B63B27/10—Arrangement of ship-based loading or unloading equipment for cargo or passengers of cranes
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B66—HOISTING; LIFTING; HAULING
    • B66C—CRANES; LOAD-ENGAGING ELEMENTS OR DEVICES FOR CRANES, CAPSTANS, WINCHES, OR TACKLES
    • B66C23/00—Cranes comprising essentially a beam, boom, or triangular structure acting as a cantilever and mounted for translatory of swinging movements in vertical or horizontal planes or a combination of such movements, e.g. jib-cranes, derricks, tower cranes
    • B66C23/18—Cranes comprising essentially a beam, boom, or triangular structure acting as a cantilever and mounted for translatory of swinging movements in vertical or horizontal planes or a combination of such movements, e.g. jib-cranes, derricks, tower cranes specially adapted for use in particular purposes
    • B66C23/36—Cranes comprising essentially a beam, boom, or triangular structure acting as a cantilever and mounted for translatory of swinging movements in vertical or horizontal planes or a combination of such movements, e.g. jib-cranes, derricks, tower cranes specially adapted for use in particular purposes mounted on road or rail vehicles; Manually-movable jib-cranes for use in workshops; Floating cranes
    • B66C23/52—Floating cranes
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B63—SHIPS OR OTHER WATERBORNE VESSELS; RELATED EQUIPMENT
    • B63B—SHIPS OR OTHER WATERBORNE VESSELS; EQUIPMENT FOR SHIPPING 
    • B63B17/00—Vessels parts, details, or accessories, not otherwise provided for
    • B63B2017/0072—Seaway compensators

Definitions

  • the present invention relates to a crane control with active Seegangs merge for a crane arranged on a float, which has a lifting mechanism for lifting a hanging on a rope load.
  • Such crane controls are needed in order for a float on such as.
  • a semi-submersible or a bark-mounted crane to compensate for the undesirable influences of the sea state on the movement of the load, which otherwise affect the safety and accuracy of the stroke.
  • Object of the present invention is therefore to provide an improved crane control with active Seegangs Colour available.
  • the present invention thus provides a crane control with active Seegangs judge for a crane arranged on a float, which has a hoist for lifting a hanging on a rope load available.
  • the crane control in this case has a measuring device, which determines a current seaway movement from sensor data.
  • a prediction device is provided, which determines a future movement of the load suspension point on the basis of the determined current seaward movement and a model of the seaway movement predicts.
  • a path control of the load is provided, which at least partially compensates for the movement of the load through the seaway by the control of the hoist of the crane due to the predicted movement of the load suspension point.
  • the prediction device By means of the prediction device according to the invention, it is thus possible to take into account the future movement of the load suspension point in the control of the lifting mechanism on the basis of the ascertained current seaward movement and a model of the swaying motion, so that this movement of the load suspension point is compensated by a change in the rope length and the load of the intended Train follows.
  • the path control based on the predicted by the forecasting device future movement of the load suspension point leads to a significantly improved Seegangs sail compared to a path control, which is based solely on the current movement of the load suspension point. This is due, in particular, to the fact that the actuators of a crane have high dead times and considerable time constants of up to 0.5 seconds, especially in the case of heavy loads.
  • the forecasting device therefore has a forecast horizon of more than 0.5 seconds, advantageously more than one, and more advantageously more than 2 seconds, so that despite the dead times and time constants of the hoist, a secure compensation of the movement of the load suspension point due to the swell of the Float can be made.
  • the controller takes into account the predicted movement of the load suspension point and the dead times of the hoist when it is controlled.
  • the desired trajectory of the load which of a rail planning z. B. is generated due to control commands of an operator or due to an automatically scheduled expiration of the stroke.
  • the web control now ensures according to the invention that of the railway planning provided path of the load in spite of the movement of the load suspension point, which is caused by the swaying motion of the float, is complied with.
  • the crane control according to the invention can thus ensure an exact positioning of the load. Furthermore, it is ensured that the hub does not overload the rope or the crane.
  • the model of the swell movement used in the prediction device is independent of the properties, in particular of the design and dynamics of the floating body.
  • the crane control according to the invention can be used flexibly for a large number of floats.
  • the crane can be mounted on different ships, without the Seegangs merge the crane control would have to be adapted for each of these, which would be very costly in a dependent on the characteristics of the ship modeling.
  • the model is thus created independently of the characteristics of the floating body based solely on the measured sea state movement, to which the periodic portions of the sea state movement are used. For this purpose, not only the current seaward movement, but the course of the seaward movement over a certain period of time is analyzed.
  • the prevailing modes of the wave motion are determined from the data of the measuring device, in particular via a frequency analysis, and based on the thus determined prevailing modes created a model of the sea state.
  • the forecasting device thus analyzes the seaward movement and determines the frequencies which determine the movement of the floating body through the sea. For example, here a Fourier analysis of the Seegangsdoch be performed, from which by peak detection, the prevailing modes are determined.
  • at least the three strongest modes of the swaying motion are considered, furthermore advantageously up to ten modes.
  • the modes are determined by a longer-term observation of the seaward movement, the analysis being based on a period of the preceding seaward movement of several minutes range, eg to the previous five minutes. Based on the prevailing modes, the forecasting device thus creates a preliminary model of the seaway, which is based on a longer-term observation of the seaway movement.
  • the model thus created is continuously parameterized on the basis of the data of the measuring device, in particular via an observer, wherein in particular the amplitude and phase of the modes are parameterized.
  • this model is constantly adapted to the current data of the measuring device.
  • the forecasting device continuously updates the amplitudes and phases of the individual modes used in the model.
  • the weighting of the individual modes in the model can be continuously updated.
  • This model is then constantly updated via an observer circuit by re-parameterizing the amplitude and phase of the modes by comparing the model's predicted seaward motion and the measured seawall motion. The prevailing modes are not changed by the observer.
  • the model is updated whenever the prevailing modes of the sea state change.
  • This change in the prevailing modes of the sea state is detected by a longer-term observation of the sea state movement, whereby the model is updated when the deviation of the modes used in the model with the actual prevailing modes has exceeded a certain threshold.
  • an update may be the prevailing one Modes can be provided in the model of the sea state every 20 seconds.
  • the path control according to the invention on a pilot control, which is stabilized on the basis of sensor data.
  • the path control thus controls the hoist based on the predicted movement of the load suspension point so that a planned path of the load is maintained as accurately as possible.
  • sensor data are used, so that a more precise control of the lifting mechanism is possible by means of an observer circuit.
  • the path control is based on a model of crane, rope and load, in which a change in the rope length due to the expansion of the rope is taken into account. Since rope lengths of up to 4,000 m can occur, in particular at depth strokes, a large expansion of the rope can occur, which is now taken into account in the path control according to the invention.
  • the path control is based on a model of crane, rope and load, which takes into account the dynamics of the hoist and / or the rope and in particular based on a physical model of the dynamics of the system of hoist, rope and / or load.
  • the dynamics of the hoist is taken into account, so that the feedforward z. B. reaction times and inertia of the hoist taken into account.
  • the dynamics of the rope and load system it is advantageously treated as a damped oscillator.
  • the resulting dynamics is modeled in the system and enters the feedforward control of the path control according to the invention, whereby the dynamic change in length of the cable can be taken into account in the feedforward control.
  • a force sensor for measuring the force acting in the cable and / or on the hoisting gear, the measured data of which enter into the path control and via which, in particular, determines the rope length becomes.
  • a direct feedback of the position of the load on the path control for stabilization is not possible because the position of the load itself can be difficult to measure.
  • the force is measured in the rope or on the hoist and used to stabilize the control.
  • the rope length can be reconstructed from the force in the rope on the basis of the model of the dynamics of the rope and load system and the position of the load can be determined.
  • the measuring device of the present invention comprises gyroscopes, acceleration sensors and / or GPS elements, from the measured data of the current sea state movement is determined.
  • gyroscopes are used according to the invention.
  • An absolute position determination is not possible with such gyroscopes, but for the active Seegangs terminate but also not necessary, since only the relatively high-frequency movements of the float due to the sea state movement must be considered, while a slow drift is not significant.
  • the angular velocities or the position of the measuring point on which the gyroscopes are arranged are then determined from the data of the gyroscopes by integration once or twice.
  • the sensors of the measuring device are arranged on the crane, in particular on the crane foundation, the measuring device advantageously determining the movement of the load suspension point on the basis of a model of the crane and the relative movement of load suspension point and measuring point. If the sensors are arranged on the foundation of the crane, they move along with the float and thus only measure the seaway movement of the float. Based on the model of the crane, the movement of the load suspension point can be determined from this swaying motion of the floating body.
  • the swaying motion of the floating body in the forecasting device is used to predict the future movement of the floating body and from this the future movement of the load suspension point on the basis of this future movement of the floating body is determined on the basis of the model of the crane.
  • the arrangement of the sensors of the measuring device on the crane thereby ensures that the crane control according to the invention can be used flexibly and independently of the properties of the floating body.
  • the forecasting device merely determines the future movement of the load suspension point in the vertical.
  • a particularly simple forecasting device is provided, which nevertheless provides the decisive data for compensating for the swaying motion with comparatively little constructive effort.
  • the present invention further comprises a crane with a crane control as described above.
  • this is a ship crane.
  • the crane according to the invention advantageously comprises a slewing gear and a luffing gear, which are likewise controlled by the crane control according to the invention.
  • the present invention also includes a floating body with a crane, as described according to the invention.
  • a floating body with a crane as described according to the invention.
  • it is advantageously a ship with a ship's crane.
  • the present invention further includes a method of controlling a crane mounted on a float having a hoist for lifting a load suspended from a rope, comprising the steps of: determining the current sea motion from sensor data, predicting future movement of the load suspension point based on the determined current one Seegangsterrorism and a model of the seaward movement, and at least partially balancing the movement of the load by the sea state by the control of the Hoist of the crane due to the predicted movement of the load suspension point.
  • the procedure is as described above with regard to the crane control.
  • the method according to the invention is carried out by means of a crane control, as described above.
  • an embodiment of a measuring method will now be described, which is based on the one hand on the measurement of the movement of the ship and on the other hand on the determination of the relative position of the cantilever tip of the crane system from its foundation.
  • an inertial platform is used which measures the straight-line accelerations and rotational rates of rotation around all three axes of the ship. The following is to be completed by the sensors of the crane system.
  • a drift-free measurement of the dipping motion an extremely small phase shift in the significant frequency range of the dipping motion and a maximum measurement deviation of approximately 15% of the amplitude of the dipping motion is achieved.
  • the embodiment of a method for predicting the dipping movement of the load suspension point is based on a model of this movement.
  • the model can not be created a priori, it must be identified and parameterized online based on the measured dive movement.
  • the identification is achieved by means of a frequency analysis of the vertical movement of the load suspension point. In order to always describe them correctly with the model of the dipping movement, the identification takes place at regular intervals. An observer is used for the best possible parameterization of the modeled dipping motion. The predicted sway motion is then used to minimize the influence of the swell on the movement of the load by counter-steering with the hoist.
  • the measurement of the seaward movement of the ship is sufficient. This is understood to mean the vertical deflection of the ship around its rest position.
  • the resting position of a ship is defined as the current, mean level of the smooth sea level. Slow level changes that are below a fixed frequency limit are therefore not part of the seaway movement. This includes, for example, the level changes caused by the tides. These are clearly not to be associated with the seaway movement.
  • the present invention provides a measuring method for this purpose, which can be used in conjunction with any Active Seismic Sequence (AHC) crane system.
  • AHC Active Seismic Sequence
  • the measuring method determines the swaying motion of the load suspension point and, on the other hand, calculates a short-term prognosis for the further, temporal course of this movement.
  • the interconnection between the crane and the fixed measuring system referred to as the active sea sequencer, can be mounted on a variety of vessels without requiring significant adaptation measures.
  • this Seegangs Grande is either as a floating crane, or, but on an emergency vehicle located, to use for Tiefseehub.
  • the measurement process is completely autonomous and acts platform independent.
  • ship-specific data such as displacement, hull shape, etc. or the placement of the crane system on the deck of the ship is deliberately omitted. Therefore, the term ship is also to be understood very broadly. It is synonymous with any floating body and therefore includes barges or semi-divers.
  • the term "sequencing device” is understood as meaning a technical system which is capable of reducing the vertical load oscillations excited by the sea state.
  • the load should be kept at an equidistant distance from the seabed, regardless of whether the floating crane is on a wave crest or in a wave trough.
  • the tilting of the floating crane around the longitudinal and transverse axis which is called rolling and pitching movement, should not affect the load height. If the compensation of the unwanted load oscillation is effected purely constructively, then there is a passive segregation sequence. On the other hand, one speaks of an active swell as soon as the load vibration is deliberately counteracted by means of actuators.
  • the present measuring method is able to determine the swaying motion of the load suspension point with high resolution and without time delay. This is also achieved in offshore use, where wave heights of up to 10 m are to be expected. Slow, absolute position changes of the rest position of the ship are not of interest.
  • the prognosis of the swaying motion of the load suspension point has the goal of minimizing the negative influence of the dead times of the actuators of swell followers on the load height.
  • a position profile of the load suspension point which is the dead time of the corresponding actuator in the future, whereby a constant dead time is at best completely compensated.
  • dead times of approx. 0.2 - 0.5 s are the rule. These are based on the enormous energy which must be provided for the load movement.
  • the forecast thus satisfies a time window of about 1 s.
  • Fig. 1 is a crane ship to see, which is mainly used for installation tasks above the sea level. It can be clearly seen that floating cranes generally have a load suspension point that is far above of the sea level. Its position can be specified by the crane operator by means of operating lever, whereby the load can be accurately positioned. In Tiefseehub, however, mostly rigid crane designs are used, which have the lowest possible load suspension point. These have the advantage of not increasing the movements of the ship unnecessarily. Horizontal changes in position of the load are achieved either by actuators on the load hook, or by appropriate positioning of the mission ship.
  • the actual structure of the crane system is not important. Only the vertical position of the load suspension point must be able to be measured. However, as it is usually not possible to install the sensors directly at the load suspension point, an alternative mounting location of the sensors must be selected. Here a fortification near the crane foundation proves to be useful. On the one hand, the lowest vibrations of the crane system are to be expected here, which falsify the measurement results. On the other hand, a defined orientation of the sensors during operation is achieved here. This would not be the case for a positioning of the sensor on a moving part of the crane, for example.
  • an inertial platform (IMU Initial Measurement Unit) is used to measure the ship's motion, which is attached to the crane foundation.
  • This cost-effective and autonomous measuring unit contains three accelerometers for the measurement of straight-line ship movements, as well as three yaw-rate sensors for determining the rolling, pitching, and yawing movements of the ship.
  • the sampling frequency of the measurements is 40 Hz.
  • the relevant ship movements are, however, in a frequency range between 0.04 Hz and 1 Hz.
  • the measured variables in the entire application range of the ship's cranes are not within the range of the measurement size restriction.
  • an accurate determination of the ship's movement in all 6 degrees of freedom is possible.
  • the ship movement measurement method used for the present invention is based on the measurement signals from a single inertial platform that calculates the desired position and angle signals with integral constant cutoff filters. If a more precise measurement is sought in the course of the swell, the clear separation between measurement and prognosis also enables the measurement process to be exchanged at any time without the need for further adjustments.
  • the complete movement of the ship can be determined from the measurement signals of the inertial platform. Static bias deviations are completely eliminated and a slow drift in the measured signals is largely compensated. Due to the necessary integration of the measured values, high-frequency sensor noise is strongly suppressed, so that no additional low-pass filtering is necessary.
  • the necessary sensors are known from conventional crane controls. From the measurement of the ship's motion and the knowledge of the distance between the sensor for measuring the ship's movement and the load suspension can thus, as in Fig. 3 shown, the current movement of the load suspension point are determined.
  • the model used to predict the seaward movement is not an a priori known description of the dynamics of the ship. Rather, the model depicts the dynamics of the measured seaward motion. This is determined during the duration of the swell sequence, whereby the model is constantly being re-identified and parameterized.
  • the first step is a frequency analysis of the measured swell motion.
  • a provisional parameterization of the completely identified model is also carried out.
  • This model subsequently serves as the basis of a linear or non-linear observer and is updated at fixed intervals. This performs the exact adaptation of the model parameters taking into account the currently measured seaward movement. With the knowledge of the model, as well as its parameters, it is the task of the prediction to calculate a prediction of the seaward motion for a future time.
  • the aim of the model identification is to determine the basic structure of the model of the seaway movement.
  • the determination of the necessary number of modes N is based on an online performed, discrete Fourier analysis of the measured sea state movement at time t i and subsequent evaluation. For this purpose, the significant frequencies of the swell motion are determined by the amplitude response determined. This evaluation of the amplitude response is performed at runtime of the measurement by means of the peak detection.
  • the peak detection provides the frequencies ⁇ N of the detected modes and a first estimate of the vector of the amplitudes. The phases of the modes are then determined separately from the phase of the discrete Fourier transform. If the model is provided with these parameters, it provides the modeled seaward movement.
  • the desired parameter adaptation is equal to an estimate of the current system state.
  • the problem of the model parameterization can therefore be formulated analogously to an observation task. An observer always has the task of estimating the complete state of this route from the measured output variables of a track with sensors.
  • the sought state is determined by means of a model of the route, which is corrected on the basis of the differences between the real and simulated output signals.
  • the dive movement can be considered as a periodic movement.
  • Their model is thus formed from a superimposition of N M sinusoids, which are referred to as modes hereinafter. Each mode is described completely by its amplitude A M, k , angular frequency ⁇ M, k and phase ⁇ M, k .
  • the model still has to add a static offset z LA, off , since the rest position of the dipping movement does not have to be in the origin of the z-axis of the world coordinate system.
  • x denotes the vector of the states of the system of order n with the initial conditions x 0 at time t 0 , which are chosen to be zero without limiting the generality.
  • u stands for the p inputs of the system.
  • the matrix A is called the system matrix
  • B the control matrix
  • C the measurement matrix.
  • Equation 5.6 the system output y in Equation 5.6 is chosen so that it describes the plunge motion of the load suspension point.
  • n is the order of the system with the output y.
  • the states x and their initial conditions x 0 are located in the natural working space of a nonlinear system M n , which is described by the n-dimensional manifold.
  • the input of the system u lies in the permissible quantity of the input functions U 1 .
  • the dynamics of the system is described by the vector field f (x), which is thus the nonlinear analog of the system matrix A of the linear systems.
  • h (x) stands for the output function of the system and can be compared with the measurement matrix C of the linear systems.
  • the only output of the overall system is chosen so that it describes the dipping movement of the load suspension.
  • the aim of the model identification is to determine the basic structure of the model of the dipping movement. Since this is already specified except for the number of modes, it is only necessary to determine their number.
  • the pre-parameterization of the model has the task of adapting the parameters of the identified model as accurately as possible.
  • N M the number of parameters to be determined thus results in 3N M + 2.
  • N M the first and most important task, since it is similar to the model identification.
  • the identification and pre-parameterization of the model of the dipping movement is carried out on the basis of the measured, vertical movement of the load suspension point.
  • the structural approach is in FIG. 5 shown.
  • the determination of the necessary number of modes N M is based on an online performed, discrete Fourier analysis of the measured dipping movement at time t i and subsequent evaluation.
  • the significant frequencies of the dive movement are determined by means of the amplitude response. This evaluation of the amplitude response is performed at runtime of the measurement by means of the peak detection.
  • the peak detection supplies the frequencies of the detected modes ⁇ M, DFT, k, which are combined to the vector ⁇ M, DFT , and a first estimate of the vector of the amplitudes A M, DFT .
  • the phases of the modes ⁇ M, DFT are then determined separately from the phase of the discrete Fourier transform. If the model is provided with these parameters, it supplies the modeled dipping movement in the time range between t 0 and T, which is denoted by z LA, DFT .
  • the amplitude response A DFT, i and the phase response ⁇ DFT , i are determined from z LA (t) via the time-discrete signal z La, n .
  • the discrete Fourier transform can be applied every 10 seconds to the actual load movement of the load suspension.
  • the main task of the peak recognition is to identify the state model of the dipping motion.
  • the offset shift defines a constant minimum amplitude of the limit sequence over the entire frequency spectrum. It is formed from the product between the freely selectable design parameter c limit and the absolute maximum of the amplitude response A DFT, Max , which is determined analogously to equation 5.24.
  • the second part is a moving averaging applied to a limited frequency band of the amplitude spectrum.
  • M M . SE M SE . i
  • a DFT . i - A DFT . i - 1 > 0 ⁇ A DFT . i + 1 - A DFT . i ⁇ 0 ⁇ A DFT . i > A DFT . border . i . i 1 . ... . N DFT 2 - 1
  • the pre-parameterization of the models is now to be carried out with the set of modes M M, DFT used for the model identification. This is equal to the set of detected modes M M, SE , if N M, SE ⁇ N M, Max . Otherwise it is the subset containing the N M, Max modes with the largest amplitude.
  • M SE . i ⁇ M M . DFT i 0 . 1 . ... . N DFT 2 ,
  • the selection of the dominant modes is carried out in the present work by a sorting algorithm applied to the amplitudes of the modes. It should be noted that the assignment between the amplitude, frequency and phase of a mode is not lost by resorting the modes.
  • the amplitude response of this movement is again used.
  • the DC component of the sequence of measurement data provided for the discrete Fourier transformation corresponds to the first value of the amplitude response.
  • the determination of the phases of the individual modes completes the pre-parameterization of the model of the dipping movement. They are determined by evaluating the phase response.
  • this expression is greatly simplified and can ultimately be represented as a function of a single value of the amplitude response ADFT, i and the phase response ⁇ DFT, i .
  • This simplification is based on the property that in the image area of the Fourier transformation, a pure sine wave is described by a complex conjugate number of numbers whose values are located at the ith and N DFT -i th position of the sequence. To clarify the further steps, this pair of numbers is in FIG. 6 (Representation of the i-th value of the image sequence and its complex conjugate value at the point N DFT - i).
  • M DFT . i ⁇ M M . DET 2 ⁇ A DFT . i ⁇ cos ⁇ DFT . i .
  • An observer always has the task of estimating the complete state of this route from the measured output variables of a track with sensors.
  • the desired state x is determined by means of a model of the distance, which is corrected on the basis of the differences between the real y and simulated output signals.
  • FIG. 7 In this case, a signal flow diagram of such an observer is shown.
  • the linear observer design is based on the state model of the dipping motion according to equation 5.6.
  • the linear Kalman-Bucy filter is one of the most popular used observers which build on the structure of the Luenberger observer.
  • the design parameters Q and R are symmetrical and positive definite. Its dimensions are determined by the number of system states and the outputs of the observer model.
  • Q is to be chosen as a (2N M, DFT + 1 x 2N M, DFT + 1) matrix and R as a scalar. If only the diagonal elements of the covariance matrix Q are described, due to the prevailing structure of the system matrix A, the dynamics of the error correction for each mode can be specified separately. The larger the track of the k-th block matrix Q k is selected, the faster is a correction of the corresponding deviations of the states ⁇ x k of the mode.
  • the design parameter R influences the dynamics of all states equally. The smaller R is selected, the more dynamic the observer reacts to deviations between the measured and simulated dive movement.
  • the covariance matrix Q of this work used for the estimation of the individual modes of the dive movement is constructed according to the following equation.
  • Q Q 1 0 ⁇ ⁇ 0 0
  • Q 2 ⁇ ⁇ ⁇ ⁇ ⁇ ⁇ ⁇ ⁇ Q N M .
  • DFT 0 0 ⁇ ⁇ 0 c off
  • the factor c k of the covariance matrices Q k is determined as a function of the angular frequency of the associated mode.
  • Table 5.2 Entries of the covariance matrix ⁇ u> Q ⁇ / u> as a function of the angular frequency ⁇ ⁇ i> ⁇ sub> M, DFT, k ⁇ / sub> ⁇ /i> ⁇ Min ⁇ ⁇ M, DFT, k ⁇ Max ⁇ min [ rad / s ] ⁇ Max [ rad / s ] ⁇ min [ rad / s ] ⁇ Max [ rad / s ] ⁇ min [ rad / s ] ⁇ Max [ rad / s ] ⁇ min [ rad / s ] ⁇ Max [ rad / s ] ⁇ min [ rad / s ] ⁇ Max [ rad / s ] ⁇ min [ rad / s ] ⁇ Max [ rad / s
  • Equation 5.11 the state model of the dip motion as given in Equation 5.11 is to be used.
  • the Extended Kalman Filter is a nonlinear extended variant of the Kalman-Bucy linear filter.
  • n nonlinear filter equations For the realization of the extended Kalman filter, it is therefore necessary to integrate the n nonlinear filter equations.
  • the Jacobi matrices H (t) and F (t) are to be calculated, as well as the n (n + 1) / 2 differential equations of the symmetric covariance matrix P to be solved. All of this has to be done online, which greatly increases the amount of computation required with the system's order.
  • F t F 1 0 ⁇ ⁇ 0 0 F 2 ⁇ ⁇ ⁇ ⁇ ⁇ ⁇ ⁇ ⁇ F N M .
  • the block matrices H k of the system output and the diagonally arranged block matrices F k are constructed as described below.
  • the design parameters of the extended Kalman filter must be specified. These consist of the covariance matrices Q and R, which are to be chosen symmetrically and positively definite. In addition, it is necessary to set a suitable initial condition for P 0 . Q is thus again set as a diagonal matrix, whose entries are weighted according to the frequency of the associated mode.
  • the structure of the covariance matrix Q as given in equation 5.110, thus equals the matrix Q used in the linear case.
  • Q Q 1 0 ... ... 0 0 Q 2 ⁇ ⁇ ⁇ ⁇ ⁇ ⁇ ⁇ Q N M . DFT 0 0 ... ...
  • the calculation of the parameters of the modes takes place inversely to the calculation of the initial state ⁇ x 0 of the linear, as well as the nonlinear state model.
  • the calculation basis used is the estimated state of the model ⁇ x (T) at time T, ie the present. This is adapted over the entire time interval of the observation of t 0, Obs ⁇ t ⁇ T on the basis of the latest measurement data of the dipping motion. Thus, all changes occurring up to this time in the dynamics of the dipping motion are considered.
  • the phase of the modes ⁇ M, Obs, k consistent with the modeling of the dipping motion, refers to the time t 0 .
  • Equation 5.102 the states of the extended Kalman filter are defined as shown below.
  • the parameters A M, Obs, k , ⁇ M, Obs, k , ⁇ M, Obs, k and z LA, Obs to be used for the prediction of the dive motion are thus to be calculated in the sequence given below.
  • a sea-tracking system based on a forecast of seaward motion and an inversion-based control strategy is proposed.
  • the control objective is to allow the payload suspended on a rope to follow a desired reference path in a fixed earth coordinate system without being affected by the seaward motion of the ship or watercraft. Therefore, a combination of a control unit, which decouples the disturbance of the track tracing, and a forecasting algorithm presented and evaluated with simulation and measurement results.
  • the wave-induced movements of the ship / vessel cause critical tension on the rope.
  • the tension should not be below zero to avoid slack rope situations.
  • the peak value must not exceed a safety limit. Therefore, wake tracking systems are used to improve the operational readiness of offshore installations during rough sea conditions.
  • the vertical movement of the payload can be significantly reduced, which makes an exact positioning of the load possible.
  • the present invention provides a sea tracking system based on the forecast of ship / vessel motion and an inversion-based control strategy.
  • the first is to let the load follow a desired reference trajectory resulting from the hand lever signals of the operator is generated in a fixed earth reference coordinate system.
  • the load should move in this coordinate system at the assigned reference speed decoupled from the wave-induced motion of the ship.
  • the second requirement is a modular crane with swell. This means that the crane systems used for offshore installations can be built on many different types of ships or vessels.
  • the ship's / vessel's vertical motion estimation and prediction algorithm must be independent of the type of vessel / vessel.
  • Fig. 8 shows the general control structure.
  • the estimation and forecast of the movement of the ship / watercraft is presented. Therefore, a model is formulated based on the prevailing modes of sea state motion. The modes are obtained by a fast Fourier transform and a peak detection algorithm. The estimation and prognosis is done by a Kalman filter. Simulation and measurement results are presented.
  • the presently considered Seegangs mergesystem consists basically of a hydraulic-powered winch, a crane-like structure and hanging on a rope load. To model the system, it is assumed that the crane structure is a rigid body. The payload suspended from a rope can be approximated by a spring-mass-damper system (see Fig. 9 ).
  • rope + m load , ⁇ ( z ) is the tension of the rope, E is the Young's modulus, F ( z ) the static force acting on the rope at position z , A rope the sectional area of the rope, g the gravitational constant, depth the distance of the load to the sea level, m l , rope and m load the mass of the rope per meter or the mass of the payload.
  • the actuator for the Seegangs mergesystem is the hydraulic-powered winch.
  • the dynamics of this actuator can be approximated with a first order system.
  • ⁇ ⁇ W - 1 T W ⁇ ⁇ ⁇ W + 2 ⁇ ⁇ K V , W i W ⁇ V mol .
  • W ⁇ T W ⁇ u W ⁇ W and ⁇ W are the angular acceleration or velocity of the winds, T W the time constant, V mot, W the volume of the hydraulic motor, u W the input voltage of the servo valve and K V, W the proportional constant of the flow rate to u W.
  • the dynamic model of the system is derived in the following form.
  • the disturbance d is defined as the 4th derivative of the seaway movement.
  • the relative degree of the system is equal to the relative degree of disturbance, and isidori is able to decouple the disturbance.
  • the operator L f represents the Lie derivative along the vector field f resp .
  • L g along the vector field g .
  • the track sequence controller decoupling the disturbance may be formulated based on the method of linearization of input / output.
  • Equation (10) offsets the error between the reference tracks y ref and the derivatives of the output y .
  • the gains of the feedback values k i are obtained by the pole assignment method.
  • the control structure is in Fig. 8 illustrated.
  • the first part of this section suggests how to estimate the overall vessel / vessel movement by measuring with an Initial Measurement Unit (IMU).
  • IMU Initial Measurement Unit
  • the key requirement for this estimate is that all ship-specific information should be used.
  • the second part explains a short-term forecasting problem. Here only the seaward movement of the cranes is forecasted. This reduces the complexity of 6 degrees of freedom to just one without losing required information.
  • the prognosis is also completely independent of a ship model.
  • the rigid body of the ship / watercraft has 6 degrees of freedom.
  • IMU the displacement of the ship from the steady state can be measured with high precision.
  • These cost-effective stand-alone motion sensors feature 3 accelerometers for measuring surf, swings, and swell, as well as 3 yaw rate sensors for rolling, pounding, and yawing. To obtain the desired relative position of the ship, a double integration of the acceleration signals and a simple integration of the rotation signals are required. To reduce typical errors such as sensor noise, bias and misalignment of the accelerometers, and to ensure stable integration, the signals can be processed.
  • the structure of the forecasting procedure is in Fig. 10 shown.
  • a Fast Fourier Transform FFT
  • the analyzed length and sampling time of the input signal are chosen so that the maximum frequency of the wave motion can be detected and the desired resolution of the frequencies is achieved.
  • the peaks of the resulting amplitude response over frequency A (f) are then extracted by a peak detector. This results in a first estimate of the amplitudes and frequencies of the mode stored in the respective parameter vectors A FFT and F FFT .
  • the mode size N is equal to the number of detected peaks.
  • the phases ⁇ FFT of the mode can also be defined.
  • the model of seaward motion described in (11) can be parameterized.
  • the evaluation of the real measured wave motion data shows the necessity of a constantly updated model (see Fig. 11 ).
  • an observer adjusts the parameter vectors by comparing the measured seaward motion w ( t ) with the modeled seaward motion. This is necessary because the FFT only detects averages of a long period of time, while the observer can take the last changes into account.
  • these new parameter vectors denoted by A Obs , f Obs and ⁇ Obs the prognosis of the seaward movement can be made by reusing (11).
  • the design of the observer depends on a Seegangsschismodell, which is described by a set of ordinary differential equations (ODEs, abbreviated to English Ordinary Differential Equations).
  • ODEs ordinary differential equations
  • the seaward movement can be modeled as a non-linear system that allows the observer to estimate all the parameters required for the forecast of the sea state.
  • this method is not usable on more modern computers.
  • a linear model can be used instead.
  • the frequencies of the mode are not adapted again. However, these are estimated by the FFT anyway with great precision.
  • a Kalman filter can be used.
  • the Q used as a design parameter is chosen to be a diagonal matrix that offends fast modes more than slow ones, whereas R equally affects all modes.
  • Fig. 12 shows the predicted and measured seaward movement over time.
  • the forecast interval T Pred was chosen to be 1 second.
  • the predicted seaward movement was then postponed.
  • an error-free predicted signal would match the measured signal.
  • Fig. 13 is the simulated sequential behavior of the Seegangs mergesystems visible.
  • the reference track is generated by a hand lever signal and the crane is subjected to a seaward movement.
  • a linearizing controller without stabilization was used for this simulation.
  • the excitation of the suspension point movement of the payload which in the first graph of Fig. 14 is shown to be reduced by a factor of 5.
  • the pump / motor system was simulated with a dead time, which is not taken into account in the design of the control unit.
  • Fig. 15 shows the follow-up behavior of the payload position in open circuit with a seaway forecast in the range of dead time of the actuator (0.2 seconds). It can be seen that good sea balance results are achieved as soon as the linearizing controller is activated, which occurs at 250 seconds. There is a clear improvement in comparing the consequences with and without a seaway forecast.
  • the present invention provides an approach to balancing seaward motion in offshore cranes.
  • the dynamic model of the balancing actuator (hydraulically driven winch) and the load hanging on a rope are derived.
  • a web follower is being developed.
  • the seaward motion is defined as a time-variant disturbance and is analyzed for decoupling conditions. With a model extension, these conditions are fulfilled and an inversion-based decoupling tax law is formulated.
  • an observer is used to reconstruct the unknown state from a force measurement.
  • the compensation can be calculated by forecasting the Seegangsdoch be improved.
  • a forecasting method is proposed in which no ship / watercraft models or characteristics are required. The simulation and measurement results validate the Seegangs mergebacter.

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  • Engineering & Computer Science (AREA)
  • Mechanical Engineering (AREA)
  • Chemical & Material Sciences (AREA)
  • Combustion & Propulsion (AREA)
  • Ocean & Marine Engineering (AREA)
  • Feedback Control In General (AREA)
  • Control And Safety Of Cranes (AREA)
  • Jib Cranes (AREA)
  • Navigation (AREA)
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EP2550226A1 (fr) * 2010-03-24 2013-01-30 National Oilwell Norway AS Procédé de réduction de charges dynamiques de grues
EP2636635A1 (fr) * 2012-03-09 2013-09-11 Liebherr-Werk Nenzing GmbH Commande de grue avec mode de traction de câble
EP2636636A1 (fr) * 2012-03-09 2013-09-11 Liebherr-Werk Nenzing GmbH Commande de grue avec répartition de la grandeur du dispositif de levage réduite par cinématique
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US10470361B2 (en) 2013-09-18 2019-11-12 Horsch Leeb Application Systems Gmbh Device for discharging fluid and/or solid active materials and method for controlling such a device
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DE102014224204A1 (de) 2014-11-27 2016-06-02 Robert Bosch Gmbh Verfahren und Vorrichtung zum Führen einer Last gemäß einer Soll-Absolut-Trajektorienvorgabe mittels eines Fahrzeugs, welches einer Fluidbewegung eines Fluids ausgesetzt ist
US10561061B2 (en) 2015-03-02 2020-02-18 Horsch Leeb Application Systems Gmbh Device for spreading liquid and/or solid active agents and method for controlling such a device
EP3335977B1 (fr) 2016-12-15 2019-06-19 Robert Bosch GmbH Procédé et dispositif de compensation de la houle
DE102016225093A1 (de) 2016-12-15 2018-06-21 Robert Bosch Gmbh Verfahren und Vorrichtung zur Wellengangskompensation
EP3335977A1 (fr) 2016-12-15 2018-06-20 Robert Bosch GmbH Procédé et dispositif de compensation de la houle
EP3854747A1 (fr) * 2020-01-22 2021-07-28 National Oilwell Varco Poland Sp.z o.o. Dispositif, système et procédé pour filtrer un signal de position dans la compensation active du tangage
CN113526375A (zh) * 2021-06-25 2021-10-22 上海海事大学 一种波浪补偿功能验证装置
CN113526375B (zh) * 2021-06-25 2023-11-24 上海海事大学 一种波浪补偿功能验证装置
CN113687597A (zh) * 2021-09-24 2021-11-23 大连海事大学 一种基于二阶波浪漂移力的无人船路径跟踪方法
CN113687597B (zh) * 2021-09-24 2023-11-17 大连海事大学 一种基于二阶波浪漂移力的无人船路径跟踪方法
CN113879460A (zh) * 2021-10-11 2022-01-04 中船澄西船舶修造有限公司 液货船用传感器安装装置

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US20100230370A1 (en) 2010-09-16
DE102008024513A1 (de) 2009-11-26
CN101585486B (zh) 2016-12-21
DE102008024513B4 (de) 2017-08-24
US8235231B2 (en) 2012-08-07
CN101585486A (zh) 2009-11-25

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