Crane

Abstract

To provide a crane that is able to restrict an amount of load swing.SOLUTION: A crane has: a hoisting device that vertically moves a suspended load attached to a rope; and a horizontally-moving device that has the hoisting device mounted thereon and horizontally moves the suspended load. A crane control device of the crane has a state inference device that infers a device state from pieces of operation information of respective motors of the hoisting device and the horizontally-moving device.SELECTED DRAWING: Figure 4

Description

[Technical Field]

[0001] The present invention relates to a crane. [Background technology]

[0002] Cranes are widely used for transporting heavy objects. Since the object being transported is suspended by ropes or other devices, load sway is inevitable during the transport process. To mitigate this, various load sway suppression technologies have been proposed.

[0003] As some examples, Patent Document 1 discloses a crane that suppresses load sway by focusing on a speed command value. Patent Document 2 discloses an acceleration / deceleration pattern for suppressing load sway. Patent Document 3 discloses estimating the state of a hoist based on a state estimation formula. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] Japanese Patent Publication No. 2022-15495 [Patent Document 2] Patent Publication No. 2021-75372 [Patent Document 3] Japanese Patent Publication No. 2022-157683 Summary of the Invention [Problem to be solved by the invention]

[0005] In recent years, there has been a demand for faster and safer crane transport. These demands are expected to become even stronger in the future. With conventional technology alone, even if the degree of improvement is the same compared to when the technology is not applied, an increase in the absolute value of the swing amount itself is unavoidable as the speed increases. Therefore, there is a need for more advanced load swing suppression technology and a way to suppress the amount of load swing than conventional technology.

[0006] Therefore, an object of the present invention is to provide a crane and a method for controlling a crane that can further suppress the amount of load sway. [Means for solving the problem]

[0007] A crane having a hoisting device that moves a load attached to a rope in the vertical direction, and a horizontal movement device that is equipped with the hoisting device and moves the load horizontally, wherein the crane control device of the crane has a state estimation device that estimates the device state from operating information of the motor of the horizontal movement device. [Effects of the Invention]

[0008] According to the crane of the present invention, it is possible to provide a crane that suppresses the amount of load swing.

[0009] Further means and effects of the present invention will become apparent throughout the entire specification below. [Brief explanation of the drawings]

[0010] [Figure 1] FIG. 1 is an explanatory diagram of an example of a crane. [Figure 2] FIG. 1 is an explanatory diagram of an example of a crane. [Figure 3] FIG. 2 is an explanatory diagram showing the positional relationship between the crane, the load, and the rope. [Figure 4] FIG. 1 is an explanatory diagram of an embodiment of the present invention. [Figure 5] FIG. 1 is an explanatory diagram of an embodiment of the present invention. [Figure 6] FIG. 1 is an explanatory diagram of a multitasking neural network of the present invention. [Figure 7A] 10 is an example of a command frequency according to the present invention and others. [Figure 7B] 10 is an example of the amount of load swing in the present invention and other cases. [Figure 8] 1 is an explanatory diagram in which the configuration of a speed command calculation device in Patent Document 2 by the same first inventor as in the present case is transcribed by the same first inventor. [Figure 9]FIG. 10 is an explanatory diagram of another embodiment of the present invention. [Figure 10] FIG. 10 is an explanatory diagram of another embodiment of the present invention. [Figure 11] FIG. 10 is an explanatory diagram of a model according to another embodiment of the present invention. [Figure 12] FIG. 10 is an explanatory diagram of another embodiment of the present invention. DETAILED DESCRIPTION OF THE INVENTION

[0011] Hereinafter, an embodiment of the present invention will be described in detail with reference to the drawings. However, the present invention is not limited to the following embodiment, and various modifications and application examples within the technical concept of the present invention are also included within its scope.

[0012] Here, the present invention is effective for all cranes that can move a suspended load horizontally, and can be applied not only to cranes that traverse and travel a suspended load using a trolley and girder (for example, overhead cranes), but also to cranes that only traverse or travel (for example, unloaders). In other words, the term "crane" used below includes all types of cranes that can move a suspended load horizontally.

[0013] Furthermore, the cargo (hanging load) transported by the crane is suspended by ropes, chains, etc., but in the present invention, any hoisting device that can be used to suspend cargo is acceptable, and the type of material, shape, etc. is not important.

[0014] Therefore, as mentioned above, the term "rope" is used as a general term for any sling used to suspend cargo. In other words, "rope" includes not only so-called ropes, but also chains, belts, wires, cables, strings, cords, and the like. [Example]

[0015] Figure 1 shows the general configuration of an overhead crane. As mentioned above, the present invention is not limited to overhead cranes. The crane 1 is composed of a runway 2 installed along the walls on both sides of a building such as a factory, a girder 3 that moves on the top of the runway 2, and a trolley 4 that moves along the underside of the girder 3.

[0016] The girder 3 and the trolley 4 are provided with wheels etc. driven by electric motors, and the girder 3 and the trolley 4 can be moved by these wheels etc. In addition, a hoisting device (hoist) 5 is provided below the trolley 4.

[0017] The hoisting device 5 is composed of an electric motor and a drum that is rotated by the electric motor and winds up the rope. By using the hoisting device 5 to wind up or lower the rope 6, a hook 7 at the end of the rope 6 is raised and lowered. A load 9 is suspended from this hook 7 directly or via a sling wire 8, and the load 9 is raised and lowered as the hook 7 is raised and lowered. In other words, the crane 1 moves the load 9 horizontally by the horizontal movement (traveling) of the girder 3 and the horizontal movement (traverse) of the trolley 4, and can raise and lower the load 9 vertically (up and down) by the hoisting device 5.

[0018] In FIG. 1, the trolley 4 and the girder 3 correspond to the "horizontal movement device", but either the trolley 4 or the girder 3 can also be the "horizontal movement device".

[0019] Figure 2 shows the configuration of the crane control device in this embodiment. For simplicity of explanation, Figure 2 shows the control of traversal by the trolley 4 and lifting by the hoisting device 5, but omits the travel by the girder 3. Also, drive units such as electric motors are omitted.

[0020] The crane control device 100 is composed of a control device 101, a traverse motor control device 300 that controls the electric motor (traverse motor) of the trolley 4, a hoisting motor control device 310 that controls the electric motor (hoisting motor) of the hoisting device 5, an operation input device 200, and a display device 210. The control device 100 is equipped with a speed command value calculation device 110 that calculates speed command values ​​for the trolley 4, hoisting device 5, etc. based on operation inputs received from the operation input device 200, and calculates and outputs speed command values ​​for the trolley 4, hoisting device 5, etc., and outputs information to the display device 210.

[0021] The control device 101 is mainly a general-purpose computer and is composed of a microprocessing unit (MPU) that executes control and arithmetic processing using built-in programs and data, a memory 102 that stores the programs and data, and an input / output control unit 103 that inputs data and signals from the outside and outputs signals processed by the MPU 101 to the outside. The control device 101, memory 102, and input / output control unit 103 are connected by a bus line 104 for sending and receiving signals and data.

[0022] The operation input device 200 is equipped with an operation terminal device 201 operated by an operator, and the operation terminal device 201 is provided with operation buttons 202 corresponding to the respective directions of movement of the suspended load: forward, backward, rightward, leftward, upward, and downward. A display device 210 displays the status of the crane, etc. The operation terminal device 201 may be connected to the control device 100 by wire or wirelessly. Furthermore, the display device 210 may be mounted in the same housing as the operation terminal device 201.

[0023] The traverse motor control device 300 and the hoisting motor control device 310 control the electric motors of the trolley 4 and the hoisting device 5 based on the speed command value output from the control device 100. Although the specific configurations of the traverse motor control device 300 and the hoisting motor control device 310 are not shown, they are configured by a general-purpose computer, an inverter circuit, etc., similar to the control device 100.

[0024] Furthermore, the traverse motor control device 300 and the hoisting motor control device 310 may be mounted in the same housing as the control device 100. Although omitted in Fig. 2, the control device 100 outputs a speed command value not only for the trolley 4 and the hoisting device 5 but also for the girder 3. On the girder 3 side, an electric motor (travel motor) control device (not shown) controls the electric motor based on this speed command value.

[0025] Figure 3 is an explanatory diagram showing the relative positions of the crane, load, and rope. x0 is the trolley position, L1 is the rope length, which is the length from the center of the drum to the hook. L2 is the sling wire length, which is the length from the hook to the center of the load. L is the pendulum length, L = L1 + L2. x2 is the load swing, which is the horizontal distance from the trolley to the load. vl is the hoisting speed.

[0026] Next, the main concept of the present invention will be explained using Fig. 4. Fig. 4 is an explanatory diagram focusing on the flow of control.

[0027] The control device 100 of the present invention includes a state estimating device 60 and a load sway suppression control device 61 .

[0028] Rope length information 70 from the actual crane 50 and motor operation information 71 from the motor inverter 51 are input to the state estimation device 60. Using this information, the state estimation device 60 estimates the state of the crane apparatus. Note that 51 may be information only from the motor or only from the inverter. The state of the crane apparatus estimated by the state estimation device 60 includes at least the sway angle frequency and the load speed 80. The sway angle frequency and the load speed 80 are input to a load sway suppression control device 61. The load sway suppression control device 61 uses the sway angle frequency, the load speed 80, and a load speed command value 72 to control the motor inverter 51 to suppress load sway. Note that this control can also be performed via the traverse motor control device 300.

[0029] In this case, a major feature of the present invention is that when the state estimation device 60 estimates the state, it does not simply use a uniform, fixed model formula or the like, but estimates the state of the device by taking measures that are more in line with the actual device.

[0030] One of the methods is for state estimation device 60 to learn motor operation information 71 in advance, and as a result, estimate the device state based on the state estimation equation that has been learned in advance.

[0031] At this time, at least one of a speed command value and an applied current is used as the motor operation information.The state estimation device 60 estimates at least one of the sway angular frequency, the lifting speed, the load sway amplitude and initial phase, the load sway amount, and the load sway speed as the device state.

[0032] This allows for the construction of an optimal state estimation formula that is tailored to the actual usage and operating conditions of the crane, thereby achieving further reductions in load sway.

[0033] Another method is for the state estimation device 60 to estimate the device state from motor operation information using a neural network.

[0034] Figure 6 is an explanatory diagram of an example of a neural network used in the present invention. This neural network has an input layer 400, a shared layer 401, an independent layer 402, and an output layer 403. It can also be called a multitasking neural network. The shared layer 401 and the independent layer 402 can be one layer or multiple layers, and can be set appropriately depending on the purpose.

[0035] The input layer must have horizontal motor operation information 410. The horizontal motor operation information includes command frequency, applied current, etc. If more detailed state estimation is required, vertical motor operation information 411 can be added. The vertical motor operation information includes command frequency, rotation angle, applied current, etc.

[0036] As the output layer 403, a motor load 420, a load swing amount 421, a rope length or swing angular frequency 422, a load speed 423, etc. can be set.

[0037] The major advantage of using a neural network in this way is that it makes it possible to estimate and suppress the state of load swing with a low-cost and simple configuration and processing. This is because processing can be done simply by calculation based on the information that is originally output, without using various additional expensive sensors.

[0038] Furthermore, the recent and future trend toward higher performance and lower prices for the configuration of computing devices will advance technology in a way that exactly offsets the increase in load swing caused by increases in crane speed, so this method can be said to have high potential and availability into the future.

[0039] Even now, this method has a major advantage over conventional model-based methods: it can respond immediately to disturbances.

[0040] When a crane is moving a load, sudden disturbances can occur due to external factors, such as collisions. Even during normal operation, the object being moved starts moving from a stationary state, resulting in an initial state that differs from the normal state during movement. While conventional model-based methods were effective to a certain extent in steady-state conditions during stable movement, they were difficult to deal with when irregular situations occurred, such as the initial stage of movement or sudden disturbances.

[0041] In contrast, by using a neural network in the state estimation device 60, it becomes possible to control the disturbance so that it converges immediately even in the initial stage of such movement or in the event of an irregularity such as a sudden disturbance.

[0042] 6, by configuring the shared layer 401 so that it is independent of the output device state and the independent layer 402 so that it differs for each device state, making it a multi-tasking neural network, it becomes possible to perform appropriate state estimation and control with less computational effort. This can also be described as a multi-tasking neural network composed of a shared layer shared by all outputs and an independent layer for each output.

[0043] At this time, at least one of a speed command value and an applied current is used as the motor operation information.The state estimation device 60 estimates at least one of the load swing angular frequency, hoisting load speed, load swing amplitude / initial phase, load swing amount, and load swing speed as the device state.

[0044] Returning to Figure 4, the explanation continues.

[0045] The load sway suppression control device 61 generates a control output for suppressing load sway based on the device state estimated by the state estimation device 60 and the load speed command value 72.

[0046] At this time, it is desirable that the state estimation device 60 estimates the state of at least both the load sway angular frequency and the load speed, the load sway suppression control device 61 generates a control output for suppressing load sway from the load speed command value 72 and the estimated load speed, and the parameters of the load sway suppression control device are successively updated by information equivalent to the estimated load sway angular frequency.

[0047] 7A and 7B are explanatory diagrams comparing the cases of a crane without control, the case of Patent Document 1, and the case of applying the present invention. The dotted line represents the case without control, the dashed-dotted line represents the case of Patent Document 1, and the solid line represents the case of the present invention, in which a neural network is applied. These will be explained in detail below.

[0048] Figure 7A is a graph with time on the horizontal axis and command frequency on the vertical axis. When the crane starts moving from a stationary state, the command frequency increases. At this time, without control, as shown by the dotted line, it increases monotonically and becomes constant at a predetermined value. Note that this command frequency is an example of the frequency of the inverter that drives the motor, and the higher the command frequency, the faster the motor is rotating.

[0049] In the case of Patent Document 1, indicated by the dashed dotted line, the value is not monotonically increasing, but is controlled to gradually approach a predetermined value while repeating peaks and valleys, as shown in the example of Figure 7A. Similarly, in the case of the present invention, indicated by the solid line, the value is not monotonically increasing, but is controlled to gradually approach a predetermined value while repeating peaks and valleys, but the height and depth of the peaks and valleys are slightly different from those in Patent Document 1.

[0050] Then, when stopped, in the case of no control (dotted line), it monotonically decreases until it reaches 0. In the cases of Patent Document 1 (dashed line) and the present invention (solid line), it does not monotonically decrease, but gradually approaches 0 with repeated peaks and valleys, and the waveform, i.e., control, continues for a while even after the command frequency without control reaches 0.

[0051] Figure 7B is a graph showing the amount of load swing over time, corresponding to Figure 7A. It can be seen that without control (the dotted line), large periodic load swings occur. Even after the command frequency becomes 0 and the load movement ends, the large load swings continue for a while, and do not converge easily.

[0052] In the case of Patent Document 1, indicated by the dashed dotted line, the amplitude of the load sway is reduced compared to the case without control, and it can be seen that the load sway is reduced.

[0053] Furthermore, in the case of the present invention, shown by the solid line, the amount of load sway is even less than in the case of Patent Document 1, shown by the dashed line, and it can be seen that the time required for the load sway to stabilize at 0 after the crane has stopped, i.e., for the load to come to a complete standstill, is also shorter.

[0054] In this way, the present invention generates command values ​​that take parameter errors into account, and can reduce the residual load sway, which is the amount of load sway after the trolley stops, more than the technology disclosed in Patent Document 1. [Example]

[0055] Another embodiment of the present invention will be described with reference to FIG.

[0056] FIG. 5 shows an example in which the state estimation device 60 described in the first embodiment is used in place of the model calculation in the control device using the model calculation disclosed in FIG. 4 of Patent Document 1.

[0057] Reference numeral 100 denotes a control device, 110 denotes a speed command calculation device, 112 denotes a load sway suppression control device, 112a denotes a feedforward control device, 112b denotes a feedback control device, 113 denotes a limit processing device, 300 denotes a traverse motor control device, vp denotes a load speed, L denotes a pendulum length, V0 denotes a command frequency, and vpref denotes a target command speed.

[0058] In this embodiment, the state estimating device 60 described in the first embodiment is added to the load sway suppression control device disclosed in FIG. 4 of Patent Document 1 in place of the model equation. The state estimating device 60 estimates the load speed vp and pendulum length L. The estimated load speed vp and the estimated pendulum length L are then input to a feedback control device 112b. The estimated pendulum length L is also input to a feedforward control device 112a.

[0059] This configuration makes it possible to compensate for parameter errors, initial vibrations, and disturbances, thereby improving the performance of the control device of Patent Document 1. [Example]

[0060] Fig. 8 is an explanatory diagram in which the lead inventor of the present invention has written out the configuration of a load sway suppression control device 110 disclosed as a technical concept in Patent Document 2, which was written by the same lead inventor as the present invention. Reference numeral 111 denotes a crane model calculation device, and 112c denotes a speed command generation device.

[0061] In Patent Document 2, the configuration shown in FIG. 8 is used to perform load sway control using trapezoidal speed command values ​​as disclosed in FIG. 3 of Patent Document 2.

[0062] FIG. 9 shows a third embodiment of the present invention in which the state estimation device 60 described in the first embodiment is used in place of the crane model calculation device 111 in the configuration of FIG.

[0063] In this embodiment, the load swing speed v2, the load swing amount x2, and the pendulum length L are input as 85 from the state estimating device 60 to the speed command generating device 112c.

[0064] As a result, the configuration of this embodiment shown in FIG. 9 makes it possible to compensate for parameter errors, initial vibrations, and disturbances. [Example]

[0065] FIG. 10 is a diagram in which a parameter estimation device 90 that receives the output of the state estimation device 60 is added to the control device of FIG.

[0066] In the control system of FIG. 5, the state estimation device 60 mainly uses a neural network to estimate the state. This has the advantages of flexibility, cost, and responsiveness. However, if the neural network in the state estimation device 60 is overly reliant on, it is considered impossible to eliminate the risk of insufficiencies occurring when estimating under conditions other than those learned or when generalizing. Therefore, in this embodiment, a parameter estimation device 90 that receives the output of the state estimation device 60 is added. By adding parameter estimation using a model formula, the parameter estimation device 90 can further improve versatility and achieve stable control.

[0067] Fig. 11 is a diagram for explaining parameters to explain the crane model used in the parameter estimation device 90 in Fig. 10. It can also be said to be a diagram for explaining the crane model used in the model-type parameter estimation device.

[0068] T is the motor thrust of the horizontal movement device, S is the rope tension, F is the disturbance force on the suspended load, x0 is the position of the horizontal movement device, x2 is the amount of load swing, L is the pendulum length, m is the mass of the suspended load, and g is the gravitational constant.

[0069] Next, based on this crane model, the state of the crane is calculated using the following three model formulas.

[0070]

number

[0071]

number

[0072]

number

[0073] Equation 1 is the equation for the balance of forces in the swing direction of the suspended load. Equation 2 is the equation for the balance of rope tension. Equation 3 is the equation for the balance of trolley forces.

[0074] In the above, x2 is the amount of load sway, or the horizontal distance from the trolley to the load, x0 is the trolley position, the Greek letter theta is the load sway angle, m is the load mass, L is the pendulum length, which is the distance from the center of rope rotation to the center of the load, vl is the hoisting speed, m0 is the trolley mass, F is the disturbance force on the load, S is the rope tension, N is the trolley friction force and power loss due to transmission, and T is the trolley motor thrust (motor load).

[0075] The reason for setting a wide range of parameters in this way is to enable appropriate load sway control even when a large, sudden disturbance occurs, and the above equations 1 to 3 can also be said to be a crane model that takes disturbances into consideration.

[0076] The parameter estimation device 90 performs fitting processing of the parameters of the above model equations 1 to 3 so that the motor load obtained from the above equations 1 to 3 coincides with the estimated value of the motor load by the state estimation device 60. In this case, due to the scale of calculation, the calculation processing may be performed online or using external calculation resources such as cloud computing via a communication environment.

[0077] In other words, an example of the technical idea disclosed in this embodiment can also be expressed as follows.

[0078] A crane characterized in that it calculates the thrust of a horizontal movement device from a speed command value of the horizontal movement device based on a model equation derived from the balance of forces acting on the horizontal movement device and the suspended load, identifies parameters of the model equation so as to minimize the error between the thrust of the horizontal movement device calculated by the model equation and the thrust of the horizontal movement device estimated by a state estimation device, and derives at least one of the load sway angular frequency, amplitude and initial phase of the load sway, load sway amount, load sway speed, and hoisting speed from the identified parameters.

[0079] In this embodiment, since both the neural network and the crane model that takes disturbances into account are used in the state estimation device 60, it is possible to calculate parameters with high accuracy not only when a large sudden disturbance occurs, but also when there is a large amount of noise in the estimation formula, thereby achieving higher performance load sway control. [Example]

[0080] The configuration of this embodiment is shown in Fig. 12. In the same way that Fig. 10, which is an invention of the fourth embodiment, adds a parameter estimation device 90 that receives the output of the state estimation device 60 to the control device of Fig. 5, Fig. 12 adds a parameter estimation device 90 that receives the output of the state estimation device 60 to the control device of Fig. 9.

[0081] The parameter estimation device 90 of this embodiment can also apply the calculation processing according to Equations 1 to 3 detailed in the fourth embodiment, and can achieve the same effects as those explained in the fourth embodiment. [Example]

[0082] This embodiment is intended to add application to sudden stop control to the first to fifth embodiments.

[0083] In this embodiment, unlike the first to fifth embodiments, when state estimation is performed by the state estimation device 60 alone or by the state estimation device 60 and the parameter estimation device 90, the estimated state includes the load sway angular frequency, the load sway amplitude, and the initial phase, and the load sway suppression control device generates and outputs parameters of a trapezoidal wave speed command waveform that decelerates the horizontal movement device and cancels the load sway caused by the deceleration, from the speed of the horizontal movement device at the start of stopping, the estimated load sway angular frequency, the load sway amplitude, and the initial phase.

[0084] This makes it possible to reduce the risk of injury to people caused by load swing after the crane has stopped, for example, during an emergency stop operation due to a person entering the crane's movement path. [Example]

[0085] In this embodiment, a motor protection function is added to the first to sixth embodiments.

[0086] In this embodiment, unlike the first to fifth embodiments, when state estimation is performed by the state estimation device 60 alone or by the state estimation device 60 and the parameter estimation device 90, the motor load is estimated, and if an excessive motor load is detected, the crane is stopped.

[0087] This makes it possible to prevent damage to the motor in advance, protecting the crane itself and avoiding factory shutdowns due to crane damage.

[0088] In this case, if a motor load exceeding the rating of the motor or the rating of the crane is detected, the crane can be stopped immediately. Even in such an immediate stop, the application of the emergency stop control described in the sixth embodiment makes it possible to perform an emergency stop safely.

[0089] Furthermore, when the motor load exceeds the rated or predetermined value by a small amount, it is considered more appropriate from the perspective of ensuring safety to have the display device 210 in FIG. 2 display a warning of the excess weight and a request to prevent recurrence after the movement operation is completed, rather than immediately stopping the crane. The state estimation device 60 of the present invention, particularly by using a neural network, is also able to make such delicate judgments and learn practical boundaries. In such cases, it becomes possible to operate the crane with an internal safety factor, resulting in a crane with greater safety and operability. [Example]

[0090] In this embodiment, instead of the excessive motor load in the seventh embodiment, the crane is stopped when an excessive load swing is estimated during state estimation performed by the state estimation device 60 alone or by the state estimation device 60 and the parameter estimation device 90.

[0091] This embodiment can be realized in the same way as the seventh embodiment. Of course, each embodiment may be combined. In this embodiment, excessive load sway can be detected more reliably than in a method in which excessive load sway is detected by any individual sensor alone, so a fail-safe or safer crane can be realized.

[0092] The above describes the ideas and concepts of the present invention using various embodiments. Of course, examples realized by combining the embodiments are also included within the scope of the present invention. Furthermore, as long as the disclosed ideas and concepts are used, modifications and similar examples are also included within the scope of the present invention.

[0093] Furthermore, one example of the present invention described using the above embodiments can also be expressed as follows.

[0094] <Part 1> A crane having a hoisting device that moves a load attached to a rope in the vertical direction, and a horizontal movement device that is equipped with the hoisting device and moves the load horizontally, wherein the crane control device of the crane has a state estimation device that estimates the device state from operating information of the motor of the horizontal movement device.

[0095] <Part 2> In the crane described in <No. 1>, The state estimation device is a crane that estimates the device state from operation information of the motor based on a state estimation formula that has been learned in advance.

[0096] <Part 3> In the crane described in <Item 2>, the motor operation information is at least one of a speed command value and an applied current.

[0097] <Part 4> In the crane described in <No. 3>, The device state of the crane is estimated to be at least one of a load swing angular frequency, a load speed, a load swing amplitude and initial phase, a load swing amount, and a load swing speed.

[0098] <Part 5> In the crane described in <No. 1>, The estimated state device uses a neural network.

[0099] <Part 6> In the crane described in <No. 5>, The neural network is a multitasking neural network composed of a shared layer that is independent of the device state and an independent layer that differs for each device state.

[0100] <Part 7> In the crane described in <No. 5>, A crane that calculates the thrust of a horizontal movement device from a speed command value of the horizontal movement device based on a model equation derived from the balance of forces acting on the horizontal movement device and the suspended load, identifies parameters of the model equation so that the error between the thrust of the horizontal movement device calculated by the model equation and the thrust of the horizontal movement device estimated by a state estimation device is minimized, and derives at least one of the load swing angular frequency, load swing amplitude / initial phase, load swing amount, load swing speed, and lifting load speed from the identified parameters.

[0101] <Part 8> In the crane described in any one of <1> to <7>, A crane having a load sway suppression control device that generates a control output to suppress load sway based on a load speed command value and the estimated device state.

[0102] <No. 9> In the crane described in <No. 8>, A crane in which the estimated device state includes a load sway angular frequency and a load speed, the load sway suppression control device generates a control output for suppressing load sway from a load speed command value and the estimated load speed, and parameters of the load sway suppression control device are successively updated by information equivalent to the estimated load sway angular frequency.

[0103] <Part 10> In the crane described in <No. 8>, The estimated device state includes a load swing angular frequency, an amplitude and an initial phase of the load swing, and the load swing suppression control device generates and outputs parameters of a trapezoidal wave speed command waveform that decelerates the horizontal movement device and cancels the load swing caused by the deceleration, based on the speed of the horizontal movement device at the start of stopping, the estimated load swing angular frequency, and the amplitude and initial phase of the load swing.

[0104] <Part 11> In the crane described in any one of <1> to <7>, A crane in which the motor load is estimated by the state estimation device, and the crane is stopped when an excessive motor load is detected.

[0105] <Part 12> In the crane described in any one of <1> to <7>, The state estimation device estimates the load sway, and stops the crane when excessive load sway is detected. [Explanation of symbols]

[0106] 1: Crane 2: Runway 3: Guarda 4: Trolley 5:Hoisting device 6: Rope 7: Hook 8: Wire 9: Hanging load 50: Crane 51: Motor inverter 60: State estimation device 70: Rope length information 71: Motor operation information 80:Sway angular frequency and load speed 90: Parameter estimation device 100: Control device 101: Control and arithmetic unit 110: Speed ​​command value calculation device 111: Crane model calculation device 112: Load swing suppression control device 112a: Feedforward control device 112b: Feedback control device 112c: Speed ​​command generation device 113: Limit processing device 300: Traverse motor control device 310: Hoisting motor control device 400: Input layer 401:Shared layer 402: Independent layer 403: Output layer 410: Horizontal motor operation information 411: Up / down motor operation information 420: Motor load 421: Load swing amount 421: Rope length 423: Hanging load speed x0: Trolley position L: Pendulum length L1: Rope length L2: Sling wire length x2: Load swing amount v: Winding speed

Claims

1. A crane having a hoisting device that moves a load attached to a rope in the vertical direction, and a horizontal movement device that is equipped with the hoisting device and moves the load horizontally, wherein the crane control device of the crane has a state estimation device that estimates the device state from operating information of the motor of the horizontal movement device.

2. The crane of claim 1, The state estimation device is a crane that estimates the device state from operation information of the motor based on a state estimation formula that has been learned in advance.

3. 3. The crane according to claim 2, wherein the motor operation information is at least one of a speed command value and an applied current.

4. The crane according to claim 3, The device state of the crane estimates at least one of a load swing angular frequency, a load speed, a load swing amplitude / initial phase, a load swing amount, and a load swing speed.

5. The crane of claim 1, The estimated state device uses a neural network.

6. The crane according to claim 5, The neural network is a multitasking neural network composed of a shared layer that is independent of the device state and an independent layer that differs for each device state.

7. The crane according to claim 5, A crane that calculates the thrust of a horizontal movement device from a speed command value of the horizontal movement device based on a model equation derived from the balance of forces acting on the horizontal movement device and the suspended load, identifies parameters of the model equation so as to minimize the error between the thrust of the horizontal movement device calculated by the model equation and the thrust of the horizontal movement device estimated by a state estimation device, and derives at least one of the load swing angular frequency, load swing amplitude / initial phase, load swing amount, load swing speed, and lifting speed from the identified parameters.

8. The crane according to any one of claims 1 to 7, A crane having a load sway suppression control device that generates a control output to suppress load sway based on a load speed command value and the estimated device state.

9. 9. The crane of claim 8, A crane in which the estimated device state includes a load sway angular frequency and a load speed, the load sway suppression control device generates a control output for suppressing load sway from a load speed command value and the estimated load speed, and parameters of the load sway suppression control device are successively updated by information equivalent to the estimated load sway angular frequency.

10. 9. The crane of claim 8, The estimated device state includes a load swing angular frequency, an amplitude and an initial phase of the load swing, and the load swing suppression control device generates and outputs parameters of a trapezoidal wave speed command waveform that decelerates the horizontal movement device and cancels the load swing caused by the deceleration, based on the speed of the horizontal movement device at the start of stopping, the estimated load swing angular frequency, and the amplitude and initial phase of the load swing.

11. The crane according to any one of claims 1 to 7, A crane in which the motor load is estimated by the state estimation device, and the crane is stopped when an excessive motor load is detected.

12. The crane according to any one of claims 1 to 7, The state estimation device estimates the load sway, and stops the crane when excessive load sway is detected.

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