JP7162820B2 - Fishing net gear design support device, fishing net gear design support method, and fishing net gear design support program - Google Patents

Description

The present invention relates to a fishing net gear dynamics estimation technique for estimating the dynamics of fishing net gear in water, an operation support technique using this fishing net gear dynamics estimation technique, and a fishing net gear design technique.

In the past, it was difficult to directly grasp the dynamics of fishing nets in water. For this reason, conventionally, fishermen have relied on individual experience and intuition to control fishing operations so that fishing net gears have desired dynamics in water.

To address this problem, Patent Literatures 1, 2, and 3 describe methods of calculating dynamics of fishing net gear in water by numerical simulation.

Patent No. 3870359 Patent No. 5203252 Japanese Patent Application Laid-Open No. 2005-245300

However, in the calculation of the dynamics of fishing nets by conventional numerical simulations as shown in Patent Documents 1, 2, and 3, the dynamics of fishing nets in actual water differs greatly depending on the conditions given to the numerical simulation, such as operating conditions. I can put it away. Therefore, it is difficult to precisely design a fishing net that produces a desired shape and dynamics in water.

SUMMARY OF THE INVENTION An object of the present invention is to design a fishing net with high precision that produces a desired shape and dynamics in water.

A fishing net gear design support device according to the present invention includes a numerical simulation section, a preliminary state estimation value calculation section, a target value setting section, and a state estimation value calculation section. The numerical simulation unit performs numerical simulation using parameters indicating the design specifications of the members of the fishing net and the equation of motion of the fishing net in water to generate a mass point that constitutes a calculation model for numerical simulation of the dynamics of the fishing net in water. Calculate the position or velocity of The prior state estimation value calculation unit receives the position or velocity of the mass point, and uses the equation of motion of the fishing net gear in water to calculate the position or velocity of the mass point at the next time and the parameters indicating the design specifications of the members of the fishing net gear. Compute a prior state estimate. The target value setting unit sets a target value of the underwater shape of the fishing net gear or the load acting on the member. The estimated state value calculation unit uses the target value and the preliminary state estimated value to calculate the state estimated value of the position or velocity of the mass point at the next time and the state estimated value of the parameter indicating the design specification of the member of the fishing net gear. calculate.

According to this invention, it is possible to design, with high accuracy, a fishing net having a desired shape and dynamics in water.

FIG. 3 is a functional block diagram of a data assimilation processing unit of the fishing net gear dynamics estimation device according to the first embodiment of the present invention; 1 is a functional block diagram of a system including a fishing net gear dynamics estimation device according to a first embodiment of the present invention; FIG. BRIEF DESCRIPTION OF THE DRAWINGS FIG. 1 is an external perspective view showing one state of a vessel and a fishing net to which the fishing net gear dynamics estimation device according to the first embodiment of the present invention is attached; (A) is a graph showing estimated values and measured values of the fishing net gear dynamics estimation device according to the first embodiment of the present invention, and (B) is a graph showing the fishing net gear according to the first embodiment of the present invention. 4 is a graph showing an estimated value of the dynamics estimation device, a conventional estimated value, and an actual measured value; 4 is a flow chart showing main processing of the fishing net gear dynamics estimation method according to the first embodiment of the present invention. 4 is a flow chart of the fishing net gear dynamics estimation method according to the first embodiment of the present invention when numerical simulation is included. FIG. 7 is a functional block diagram of a system including a fishing net gear dynamics estimation device according to a second embodiment of the present invention; 6 is a flow chart of a fishing net gear dynamics estimation method according to a second embodiment of the present invention. It is a functional block diagram of an operation support device concerning a 3rd embodiment of the present invention. It is a flow chart of an operation support method concerning a 3rd embodiment of the present invention. FIG. 11 is a functional block diagram of a fishing net gear design support device according to a fourth embodiment of the present invention; FIG. 10 is a flowchart of a fishing net gear design support method according to a fourth embodiment of the present invention; FIG.

A fishing net gear dynamics estimation device, a fishing net gear dynamics estimation method, and a fishing net gear dynamics estimation program according to a first embodiment of the present invention will be described with reference to the drawings. FIG. 1 is a functional block diagram of the data assimilation processing unit of the fishing net gear dynamics estimation device according to the first embodiment of the present invention. FIG. 2 is a functional block diagram of a system including the fishing net gear dynamics estimation device according to the first embodiment of the present invention. FIG. 3 is an external perspective view showing one state of a vessel and fishing nets to which the fishing net gear dynamics estimation device according to the first embodiment of the present invention is attached.

As shown in FIG. 2 , the fishing net gear dynamics estimation device 10 includes a data assimilation processing unit 11 , an observation value acquisition unit 12 , an operating condition acquisition unit 13 , and a numerical simulation unit 14 . The fishing net gear dynamics estimation device 10 is connected to the display unit 20 and the sensor 30 . The sensor 30 comprises multiple depth sensors 311 , 312 , 313 and a receiver 32 .

A dynamic estimation system comprising such a fishing net gear dynamics estimation device 10, a display unit 20, and a sensor 30 is installed on a ship 90 having a fishing net gear 91, as shown in FIG. The fishing net 91 is composed of net-like wires made of metal or the like and wire ropes or the like for manipulating the net-like wires, and is dropped into the water from the vessel 90 and used. The shape of the fishing net 91 changes according to underwater conditions such as tides, operating conditions of the ship 90, and the like.

Fishing net gear dynamics estimation device 10 , display unit 20 , and receiver 32 are mounted on vessel 90 . A plurality of depth sensors 311, 312, and 313 are attached to fishing net gear 91, respectively. More specifically, as shown in FIG. 3, a plurality of depth sensors 311, 312, and 313 are attached to different locations on the fishing net gear 91, respectively. The positions where the plurality of depth sensors 311, 312, and 313 are attached correspond to specific positions of net geological points used in the fishing net gear dynamics estimation method.

A plurality of depth sensors 311 , 312 , and 313 measure the depth of their own devices at each observation time k and transmit the depth to the receiver 32 . A receiver 32 receives depths from a plurality of depth sensors 311 , 312 , 313 . The receiver 32 uses, for example, the depths of the plurality of depth sensors 311, 312, and 313, the distances between the plurality of depth sensors 311, 312, and 313 and the receiver 32, the position of the receiver 32, and the like to determine the observation time k Observed positions xy(k) and observed velocities vy(k) of the depth sensors 311, 312, and 313 are calculated. The observation positions xy(k) and observation velocities vy(k) of these depth sensors 311, 312, and 313 correspond to observation values of the fishing net gear at a specific net geological point used in the fishing net gear dynamics estimation method. The receiver 32 outputs the observed position xy(k) and the observed velocity vy(k) of the depth sensors 311, 312, and 313, that is, the observed value of the fishing net gear to the observed value acquisition unit 12 of the fishing net gear dynamics estimation device 10. do. The observed values of the fishing net gear may be output sequentially or may be output collectively for multiple observation times. By using the sequential output, fishing net gear dynamics estimation with high follow-up to the situation can be performed. can be done.

The observation value acquisition unit 12 acquires the observation value of the fishing net gear and outputs it to the data assimilation processing unit 11 .

The operating condition acquisition unit 13 acquires operating conditions for the vessel 90 to operate using the fishing net gear 91 from an operation control unit (not shown) of the vessel 90 . The operating condition acquisition unit 13 outputs operating conditions to the numerical simulation unit 14 .

In the case of a purse seine, for example, the operating conditions include the position, speed, and course of the ship 90, the wire rope payout length and winding length of the fishing net gear 91, the current direction and speed of the tidal current, and the fishing net gear 91 used. It consists of the positions of other vessels participating in the operation. The operating conditions can be obtained by a known method (not shown) using various sensors other than the sensor 30 .

The numerical simulation unit 14 uses operating conditions to calculate the position x(k) and velocity v(k) of the network geomass using numerical simulation based on the equation of motion of the network geomass. The positions and velocities of these net geological points correspond to the "values constituting the calculation model" of the present invention.

Such numerical simulations can be performed, for example, by a method based on the description of Japanese Patent No. 3870359, although detailed description is omitted. The equation of motion used in this numerical simulation is set by a known method using physical constants such as inertial force, additional mass force, drag force, buoyancy force, gravity force, tension force, etc. for expressing the underwater dynamics of the fishing net gear. It is These dynamic quantities are set according to the operating conditions described above and are fixed values.

The numerical simulation unit 14 outputs the position x(k) and velocity v(k) of the network geophysical point to the data assimilation processing unit 11 .

As shown in FIG. 1, the data assimilation processing unit 11 includes a preliminary state estimation value calculation unit 111 and a state estimation value calculation unit 112, and implements an extended Kalman filter.

The preliminary state estimation value calculation unit 111 sets a system model including the time update matrix A(θ) based on the equation of motion of the network geological point described above.

A system model is represented by (Formula 1).

xx(k+1)=A(θ)·xx(k)+B·vv(k) −(equation 1)
xx(k) is the state vector (known number) at time k containing the position x(k) and velocity v(k) of the network geological point, and xx(k+1) is the position x(k+1) of the network geological point. and velocity v(k+1) at time k+1 (unknowns: prior state estimates).

A(θ) is a time update matrix, which is set based on the physical constants used in the equation of motion described above, such as the drag coefficient Cd and the additional mass coefficient Cm. vv(k) is the system noise at time k and B is its error coefficient matrix. The time update matrix A(θ), system noise vv(k), and error coefficient matrix B are known numbers.

Preliminary state estimation value calculation section 111 calculates state vector xx(k+1), which is a prior state estimation value, from state vector xx(k) using (Equation 1).

Prior state estimation value calculation section 111 calculates prior state estimation values using this system model, and also calculates prior error covariance matrix P using time update matrix A(θ) and error coefficient matrix B. FIG.

Prior state estimate calculation section 111 outputs state vector xx(k+1), which is the prior state estimate, and prior error covariance matrix P to state estimate calculation section 112 .

The state estimate calculator 112 sets an observation model for the state estimate.

An observation model is represented by (Formula 2).

xyy(k)=C(θ)×xx(k)+ww(k) −(Formula 2)
xyy(k) is the observation vector at time k containing the position and velocity of the fishing net gear observation. xx(k) is the state vector at time k described above. ww(k) is the observed noise at time k. C(θ) is a transformation matrix. The observation vector xyy(k) consists of observation values of fishing net gear acquired by the observation value acquisition unit 12 . Observation noise ww(k) and transformation matrix C(θ) are known numbers.

State estimate value calculation section 112 uses each value input from preliminary state estimate value calculation section 111 and (Eq. A state estimation vector xx'(k+1) containing the velocity state estimate x'(k+1) is calculated. At this time, the state estimation value calculation unit 112 uses the Kalman gain G calculated from the prior error covariance matrix P. In other words, the state estimate calculation unit 112 corrects (corrects) the preliminary state estimate for the net geological point calculated by the preliminary state estimate calculation unit 111 using the observed value of the fishing net gear and the Kalman gain. to calculate the state estimate for the network geological point.

By performing such processing, the data assimilation processing unit 11 can estimate the positions and velocities of network geological points with high accuracy.

The estimated position state value and the estimated speed state value calculated by the data assimilation processing unit 11 in this manner are fed back to the numerical simulation unit 14, and the above-described estimation processing is repeated. As a result, the positions and velocities of network geological points can be sequentially estimated with high accuracy in a time series based on observation times.

The data assimilation processing unit 11 also outputs to the display unit 20 the state estimated value of the position and the state estimated value of the velocity of the network geological point. The display unit 20 visualizes and displays the state of the fishing net gear 91 from the state estimated value of the position of the net geological point and the state estimated value of the speed. This allows the operator to easily and accurately grasp the dynamics of the fishing net gear 91 .

Although details are omitted in the above description, the dynamics of the net geological point of the fishing net gear 91 is generally non-linear. However, a Kalman filter can be applied by employing a first order Taylor series expansion for each of position and velocity. That is, the data assimilation processing unit 11 can execute an extended Kalman filter.

Further, in the above description, the net geological point to which the extended Kalman filter is applied is only the net geological point at a specific position where the observed value of the fishing net gear is obtained. However, the numerical simulation unit 14 estimates positions and velocities for a plurality of network geological points in addition to the network geological point at a specific position. In this case, for other net geomass points other than the net geomass point at the specific position, as a pre-processing of the numerical simulation, the correction amount by the extended Kalman filter for the specific position (correction amount by the observation value of the fishing net gear) is calculated, Correction based on this correction amount may also be performed for other network geophysical points.

As described above, the fishing net gear dynamics estimation device 10 can estimate the dynamics of the fishing net gear 91 with high accuracy by performing data assimilation processing of the observed values and the estimated values. That is, the fishing net gear dynamics estimation device 10 can estimate the dynamics of the fishing net gear with less error than the actual dynamics of the fishing net gear in water.

FIG. 4A is a graph showing estimated values and measured values of the fishing net gear dynamics estimation device according to the first embodiment of the present invention, and FIG. is a graph showing an estimated value of the fishing net gear dynamics estimation device according to the present invention, a conventional estimated value, and an actual measurement value. The horizontal axis of FIGS. 4A and 4B is the observation time, and the vertical axis is the depth of the net geological point at the specific position of the fishing net gear. The conventional estimated value is an estimated value obtained by the method disclosed in Patent Document 1, and is an estimated value obtained when data assimilation processing is not performed.

As shown in FIGS. 4(A) and 4(B), by using the fishing net gear dynamics estimation device 10 according to the present embodiment, an estimated value with little error relative to the measured value is obtained without being affected by the depth. can be obtained. Further, as shown in FIG. 4B, by using the fishing net gear dynamics estimation device 10 according to the present embodiment, it is possible to calculate an estimated value with higher accuracy than the conventional estimation method.

In addition, in the above description, a mode in which a plurality of processes implemented by the fishing net gear dynamics estimation device 10 are implemented by individual functional units has been described. However, a plurality of processes to be realized by the fishing net gear dynamics estimation device 10 may be programmed and stored in storage means, and the programs may be read out and executed by an information processing device such as a CPU. In this case, the method shown in the following flow chart may be programmed.

FIG. 5 is a flow chart showing main processing of the fishing net gear dynamics estimation method according to the first embodiment of the present invention.

As shown in FIG. 5, in the fishing net gear dynamics estimation method of the present embodiment, the information processing device uses the system model described above to calculate a preliminary state estimation value regarding the dynamics of the net geological point (S101). Next, the information processing device acquires observed values relating to the dynamics of network geological points (S102). Acquisition of observed values and calculation of preliminary state estimation values are not limited to this order.

Next, the information processing apparatus uses the observation model described above to calculate a state estimation value regarding the dynamics of the network geological point from the prior state estimation value and the observation value (S103).

Further, when using numerical simulation, the processing shown in FIG. 6 may be performed. FIG. 6 is a flow chart of the fishing net gear dynamics estimation method according to the first embodiment of the present invention, which includes a numerical simulation.

As shown in FIG. 6, in the fishing net gear dynamics estimation method of the present embodiment, the information processing device uses the above-described numerical simulation to calculate values related to the dynamics of net geological points (S201). Next, the information processing apparatus uses the system model described above to calculate a preliminary state estimation value regarding the dynamics of the network geological point from the values regarding the dynamics of the network geological point (S202). Next, the information processing device acquires observed values relating to dynamics of network geological points (S203). Acquisition of observed values and calculation of preliminary state estimation values are not limited to this order.

Next, the information processing apparatus uses the observation model described above to calculate a state estimation value regarding the dynamics of the network geological point from the prior state estimation value and the observation value (S204). The information processing device feeds back the estimated state value as an input value for the numerical simulation (S205).

Thereafter, the information processing apparatus repeatedly executes the processing from step S201 to step S205 described above.

By executing such processing, it is possible to accurately estimate the dynamics of the fishing net that changes over time.

Next, a fishing net gear dynamics estimation device, a fishing net gear dynamics estimation method, and a fishing net gear dynamics estimation program according to a second embodiment of the present invention will be described with reference to the drawings. FIG. 7 is a functional block diagram of a system including a fishing net gear dynamics estimation device according to a second embodiment of the present invention.

As shown in FIG. 7, the fishing net gear dynamics estimation device 10A according to the second embodiment has a data assimilation processing unit 11A and a numerical simulation unit 14A is different. The rest of the configuration of the fishing net gear dynamics estimation device 10A is the same as the configuration of the fishing net gear dynamics estimation device 10, and the description of the same portions will be omitted.

The data assimilation processing unit 11A sets physical constants used in the above equation of motion together with the positions and velocities of network geological points as unknowns of the system model and the observation model. Specifically, at least the drag coefficient Cd and the additional mass coefficient Cm in the physical constants are set as unknowns. Then, the data assimilation processing unit 11A executes the same data assimilation processing (extended Kalman filter) as described above. As a result, the data assimilation processing unit 11A calculates the estimated state values of the physical constants together with the estimated state values of the positions and velocities of the network geological point. The data assimilation processing unit 11A feeds back the state estimated value of the physical constant to the numerical simulation unit 14A.

The numerical simulation unit 14A updates the equation of motion by using the state estimated value of the physical constant fed back, and executes the numerical simulation.

The state estimated values of the physical constants are also used in the processing in the data assimilation processing unit 11A to update a portion set based on the equation of motion, for example, the time update matrix of the system model.

By using such a configuration, the physical constants are properly adjusted according to the actual underwater conditions. Therefore, the dynamics of the fishing net gear can be estimated with higher accuracy.

In addition, in the above description, a mode in which a plurality of processes realized by the fishing net gear dynamics estimation device 10A are realized by individual functional units respectively has been described. However, a plurality of processes realized by the fishing net gear dynamics estimation device 10A may be programmed and stored in a storage means, and the programs may be read out and executed by an information processing device such as a CPU. In this case, the method shown in the following flow chart may be programmed. FIG. 8 is a flow chart of a fishing net gear dynamics estimation method according to the second embodiment of the present invention. Note that FIG. 8 is a flowchart including numerical simulation, and like the first embodiment, only the data assimilation processing portion, that is, steps S302 to S304 in FIG. 8 may be used.

As shown in FIG. 8, in the fishing net gear dynamics estimation method of the present embodiment, the information processing device uses the above-described numerical simulation to calculate values related to the dynamics of net geological points (S301). At this time, the information processing device executes the numerical simulation using the physical constants updated by the previous state estimation value, except for the first time.

Next, the information processing apparatus uses the system model described above to calculate a prior state estimate value related to the dynamics of the network geological point and a prior state estimated value of the physical constant from the values related to the dynamics of the network geological point (S302). Next, the information processing device acquires observed values relating to the dynamics of network geological points (S303). Acquisition of observed values and calculation of preliminary state estimation values are not limited to this order.

Next, the information processing apparatus uses the observation model described above to calculate state estimates regarding dynamics of the network geological point and state estimates of physical constants from the prior state estimates and observed values (S304). The information processing device feeds back the estimated state values related to the dynamics of the network geological point as input values for the numerical simulation, and feeds back the estimated state values of the physical constants as set values for the numerical simulation (S305).

Next, an operation support device, an operation support method, and an operation support program according to a third embodiment of the present invention will be described with reference to the drawings. FIG. 9 is a functional block diagram of an operation support device according to the third embodiment of the invention.

As shown in FIG. 9, the fishing net gear dynamics estimation device 10B according to the third embodiment includes a data assimilation processing unit 11B, a numerical simulation unit 14B, and a And the target net bottom depth setting unit 15 is different. The concept of basic processing executed by the data assimilation processing unit 11B and the numerical simulation unit 14B is the same as the configuration of the fishing net gear dynamics estimation device 10, and the description of the same portions will be omitted.

The operation support device 110 includes a fishing net gear dynamics estimation device 10B, a display unit 20, a sensor 30, and an operation control unit 40. The display unit 20 and the sensor 30 have the same configurations as the display unit 20 and the sensor 30 shown in the first embodiment, respectively.

The operation control unit 40 executes operation control of the ship 90 . The operating condition acquisition unit 13 acquires operating conditions used by the numerical simulation unit 14B from the operation control unit 40 .

The target net bottom depth setting unit 15 sets a target value such as a target reaching depth of the fishing net gear 91 . The target net bottom depth setting unit 15 outputs the target value of the net bottom depth to the data assimilation processing unit 11B.

The data assimilation processing unit 11B sets operating conditions together with the positions and velocities of net geological points as unknowns of the system model and observation model. Specifically, the values related to the payout length and winding length of the wire rope of the fishing net gear 91 under the operating conditions, for example, the tension with respect to the net geological point at a specific position and the tension acting on the wire rope are set to unknown values. . In addition, in the observation model, the observation value of the fishing net gear and the target value of the bottom depth of the net are set as the observation values, which are known numbers.

Then, the data assimilation processing unit 11B executes the same data assimilation processing (extended Kalman filter) as described above. As a result, the data assimilation processing unit 11B calculates the estimated state values of the operating conditions together with the estimated state values of the positions and velocities of the net geological point. The data assimilation processing unit 11B feeds back the state estimated value of the operating condition to the numerical simulation unit 14B via the operating condition acquisition unit 13.

The numerical simulation part 14B performs a numerical simulation using the state estimated value of the operating condition fed back. By using such a configuration, operating conditions are appropriately adjusted according to actual operational control. Therefore, the accuracy of calculating the dynamics of fishing net gear by numerical simulation is improved.

Also, the state estimated value of the operating condition is output to the operation control unit 40 . The operation control unit 40 performs automatic operation control of the fishing net gear 91 using the state estimated value of the operation condition. Thereby, the fishing net gear 91 can be efficiently changed into the target shape. Also, the state estimated value of the operating conditions is output to the display unit 20 . The display unit 20 displays an image of the state estimated value of the operating conditions. This allows the operator to accurately grasp the actual operating conditions. In addition, by imaging in this way, it is possible to easily grasp the difference between the actual operating state and the target operating state. At this time, the operation support device 110 may notify according to this difference. For example, when the operation support device 110 detects that this difference has exceeded the caution advisory threshold, it may issue a caution advisory notification.

In addition, in the above description, a mode in which a plurality of processes realized by the operation support device 110 are respectively realized by individual functional units has been described. However, a plurality of processes to be realized by the operation support device 110 may be programmed and stored in a storage means, and an information processing device such as a CPU may read and execute the program. In this case, the method shown in the following flow chart may be programmed. FIG. 10 is a flowchart of an operation support method according to the third embodiment of the invention.

As shown in FIG. 10, in the operation support method of the present embodiment, the information processing device uses the above-described numerical simulation to calculate values relating to the dynamics of the net geological point (S401). At this time, except for the first time, the information processing device executes the numerical simulation using the operating conditions updated by the previous state estimation value.

Next, the information processing device uses the system model described above to calculate a preliminary state estimated value regarding the dynamics of the network geological point and a preliminary state estimated value of the operating conditions from the values regarding the dynamics of the network geological point (S402). Next, the information processing device acquires observed values relating to the dynamics of the network geological point (S403). The information processing device also sets a target value for the net bottom depth (S404). Acquisition of observation values, calculation of pre-state estimation values, and setting of target values for net bottom depth are not limited to this order.

Next, the information processing device uses the observation model described above to calculate state estimates regarding dynamics of the network geological point and state estimates of operating conditions from the preliminary state estimates and observed values (S405). The information processing device feeds back the estimated state value regarding the dynamics of the network geological point as an input value for the numerical simulation (S406). The information processing device feeds back the state estimated value of the operating condition as a setting value of the numerical simulation and feeds back to the automatic operation control (S407).

Next, a fishing net gear design support device, a fishing net gear design support method, and a fishing net gear design support program according to a fourth embodiment of the present invention will be described with reference to the drawings. FIG. 11 is a functional block diagram of a fishing net gear design support device according to the fourth embodiment of the present invention.

As shown in FIG. 11, the fishing net gear dynamics estimation device 10C according to the fourth embodiment includes a data assimilation processing unit 11C, a numerical simulation unit 14C, and a The fishing net gear parameter setting section 16 and the target value setting section 17 are different. The concept of basic processing executed by the data assimilation processing unit 11C and the numerical simulation unit 14C is the same as that of the fishing net gear dynamics estimation device 10, and the description of the same parts is omitted.

The fishing net gear design support device 120 includes a fishing net gear dynamic state estimation device 10C and a display unit 20 . The display unit 20 has the same configuration as the display unit 20 shown in the first embodiment.

The fishing net gear parameter setting unit 16 sets the parameters of the fishing net gear to be designed (the design specifications of the members of the fishing net gear). The parameters of the fishing net gear to be designed include, for example, the mesh length of the net, the diameter of the net thread, and the like. The fishing net gear parameter setting unit 16 outputs the parameters of the fishing net gear to be designed to the numerical simulation unit 14C.

The target value setting unit 17 sets target values related to the behavior of the fishing net gear to be designed. Target values relating to the dynamics of the fishing net gear to be designed include, for example, target positions and target speeds of net geomass points during fishing. In addition, target values relating to the dynamics of the fishing net gear to be designed include target values of the underwater shape of the fishing net gear or the load acting on the member. The target value setting unit 17 outputs the target value to the data assimilation processing unit 11C.

The data assimilation processing unit 11C sets the position and velocity of the net geological point and the parameters of the fishing net gear to be designed as unknowns of the system model and the observation model. In addition, in the observation model, the target value of the fishing net gear to be designed is set as a known observation value.

Then, the data assimilation processing unit 11C executes the same data assimilation processing (extended Kalman filter) as described above. As a result, the data assimilation processing unit 11C calculates the estimated state values of the position and speed of the net geological point and the estimated state values of the parameters of the fishing net gear to be designed. The data assimilation processing unit 11C feeds back the estimated state values of the parameters of the fishing net gear to be designed to the fishing net gear parameter setting unit 16 .

The numerical simulation unit 14C executes a numerical simulation using the fed-back estimated state values of the parameters of the fishing net gear to be designed.

Thereafter, the above processing is repeated. As a result, the parameters of the fishing net gear to be designed are sequentially updated so that the parameters of the fishing net gear to be designed satisfy the target values of the fishing net gear to be designed. Then, when the data assimilation processing unit 11C detects that the difference between the target position and target speed of the fishing net gear to be designed and the estimated state values of the position and speed of the net geological point and the difference is less than the threshold value, the parameter of the fishing net gear to be designed is output to the display unit 20 . The display unit 20 visualizes and displays the state estimated values of the parameters of the fishing net gear to be designed.

By using such a configuration, it is possible to design a fishing net with high precision that produces a desired shape and dynamics in water.

In the above description, a plurality of processes realized by the fishing net gear design support device 120 are respectively realized by individual functional units. However, a plurality of processes implemented by the fishing net gear design support device 120 may be programmed and stored in a storage means, and the programs may be read out and executed by an information processing device such as a CPU. In this case, the method shown in the following flow chart may be programmed. FIG. 12 is a flow chart of a fishing net gear design support method according to the fourth embodiment of the present invention.

As shown in FIG. 12, in the fishing net gear design support method of the present embodiment, the information processing device uses the above-described numerical simulation to calculate values related to the dynamics of net geological points (S501). At this time, except for the first time, the information processing device executes the numerical simulation using the fishing net gear parameters updated with the previous state estimation values.

Next, the information processing device uses the above-described system model to calculate a prior state estimate value related to the dynamics of the net geological point and a prior state estimated value of the parameters of the fishing net gear from the values related to the dynamics of the net geological point (S502). ). Next, the information processing device sets target values for the fishing net gear to be designed (S503). Acquisition of observed values, calculation of pre-state estimated values, and setting of target values for the fishing net gear to be designed are not limited to this order.

Next, the information processing device uses the above-described observation model to calculate the estimated state values related to the dynamics of the net geological point and the estimated state values of the fishing net gear parameters from the preliminary state estimated values and the observed values (S504). ). If the state estimated value of the parameter of the fishing net gear does not satisfy the target value (S505: NO), the information processing device feeds back the state estimated value related to the dynamics of the net geological point as an input value of the numerical simulation, The state estimated values of the parameters are fed back as set values for the numerical simulation (S406). If the state estimated value of the fishing net gear parameter satisfies the target value (S505: YES), the information processing device outputs the state estimated value of the fishing net gear parameter to the display unit or the like (S507).

In the above description, an aspect using an extended Kalman filter is shown as data assimilation processing, but other data assimilation processing that corrects estimated values with observed values may be used.

10, 10A, 10B, 10C: Fishing net gear dynamics estimation device 11, 11A, 11B, 11C: Data assimilation processing unit 12: Observation value acquisition unit 13: Operation condition acquisition unit 14, 14A, 14B, 14C: Numerical simulation unit 15: Target net bottom depth setting unit 16: Fishing net gear parameter setting unit 17: Target value setting unit 20: Display unit 30: Sensor 32: Receiver 40: Operation control unit 90: Ship 91: Fishing net gear 110: Operation support device 111: In advance State estimated value calculator 112: State estimated value calculator 120: Fishing net gear design support device 311, 312, 313: Depth sensor

Claims (3)

Parameters of the fishing net gear under design, including mesh length and thread diameter , and the positions of the mass points constituting the calculation model used for the numerical simulation of the underwater dynamics of the fishing net gear by numerical simulation using the equation of motion of the fishing net gear in water.anda numerical simulation unit that calculates speed;
a target value setting unit for setting target values including target positions and target speeds of net geomass points during operation of the fishing net gear;
Set the parameters of the fishing net gear to be designed along with the positions and velocities of the net geological points as unknowns of the system model and the observation model, set the target values as the observed values that are known values of the observation model, and perform data assimilation. By executing the processing, state estimated values of the parameters of the fishing net gear to be designed are calculated together with the state estimated values of the position and speed of the net geomass point, and the state estimated values of the parameters of the fishing net gear to be designed are calculated by the numerical simulation unit. a data assimilation processing unit that feeds back to
A fishing net gear design support device comprising: Parameters of the fishing net gear under design, including mesh length and thread diameter , and the positions of the mass points constituting the calculation model used for the numerical simulation of the underwater dynamics of the fishing net gear by numerical simulation using the equation of motion of the fishing net gear in water.andcalculate the speed,
setting a target value including a target position and a target speed of the net geomass point during operation of the fishing net gear;
Set the parameters of the fishing net gear to be designed along with the positions and velocities of the net geological points as unknowns of the system model and the observation model, set the target values as the observed values that are known values of the observation model, and perform data assimilation. By executing the processing, the estimated state values of the position and speed of the net geomass point and the estimated state values of the parameters of the fishing net gear to be designed are calculated, and the estimated state values of the parameters of the fishing net gear to be designed are applied to the numerical simulation. provide feedback,
Fishing net tool design support method. Parameters of the fishing net gear under design, including mesh length and thread diameter , and the positions of the mass points constituting the calculation model used for the numerical simulation of the underwater dynamics of the fishing net gear by numerical simulation using the equation of motion of the fishing net gear in water.anda process of calculating velocity;
a process of setting target values including target positions and target speeds of net geomass points during operation of the fishing net gear;
Set the parameters of the fishing net gear to be designed along with the positions and velocities of the net geological points as unknowns of the system model and the observation model, set the target values as the observed values that are known values of the observation model, and perform data assimilation. By executing the processing, the estimated state values of the position and speed of the net geomass point and the estimated state values of the parameters of the fishing net gear to be designed are calculated, and the estimated state values of the parameters of the fishing net gear to be designed are applied to the numerical simulation. feedback process;
A fishing net gear design support program that causes the information processing device to execute

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