Method and device for determining installation information of train flexible pipe, electronic equipment, train, storage medium and program product

Abstract

The invention provides a method and device for determining installation information of a train flexible pipe, electronic equipment, a train, a storage medium and a program product, and relates to the technical field of rail transit. The method comprises the following steps: outputting target simulation data corresponding to a target flexible pipe by utilizing a train flexible pipe simulation model; the installation information of the target flexible pipe in the train is determined according to the target simulation data, the train flexible pipe simulation model is determined through the target parameters, and the step of determining the target parameters of the train flexible pipe simulation model comprises the substeps that the target flexible pipe is fixed to pose test equipment according to preset installation constraint conditions; acquiring a plurality of first pose data and a plurality of second pose data of the target flexible pipe acquired by pose test equipment; acquiring initial parameters of a train flexible pipe simulation model for the target flexible pipe; and adjusting the initial parameters according to the plurality of first pose data and the plurality of second pose data to obtain target parameters of the train flexible pipe simulation model.

Description

Technical Field

[0001] This disclosure relates to the field of rail transit technology, and more specifically, to a method, apparatus, electronic device, train, storage medium, and program product for determining train flexible tube installation information. Background Technology

[0002] To design the installation information of flexible tubes on trains, the relevant methods are usually designed by designers based on experience in the early design process and verified in the vehicle production stage, such as verifying the rationality of the spatial orientation of the flexible tubes through on-site surveys and analysis.

[0003] In the process of realizing the present invention, the inventors discovered that the related technology has at least the following problems: in the related methods, if the flexible tube needs to be modified, it requires the modification of multiple parts, which is extremely costly, and the design involves multiple departments working together, resulting in low work efficiency. Summary of the Invention

[0004] In view of this, this disclosure provides a method, apparatus, electronic device, train, storage medium, and program product for determining train flexible tube installation information.

[0005] One aspect of this disclosure provides a method for determining the installation information of a train flexible tube, comprising: for a target flexible tube to be installed on a train, outputting target simulation data corresponding to the target flexible tube using a train flexible tube simulation model; determining the installation information of the target flexible tube on the train based on the target simulation data, wherein the train flexible tube simulation model is determined by target parameters, and determining the target parameters of the train flexible tube simulation model includes: fixing the target flexible tube to a posture testing device according to preset installation constraints; acquiring multiple first posture data and multiple second posture data of the target flexible tube collected by the posture testing device, wherein the multiple first posture data are used to simulate the static limit position and static limit attitude of the target flexible tube when the train is stationary, and the multiple second posture data are used to simulate the maximum range of motion of the target flexible tube when the train is running; acquiring the initial parameters of the train flexible tube simulation model for the target flexible tube; and adjusting the initial parameters based on the multiple first posture data and multiple second posture data to obtain the target parameters of the train flexible tube simulation model.

[0006] According to embodiments of this disclosure, acquiring multiple first pose data and multiple second pose data of a target flexible tube collected by a pose testing device includes: controlling the pose testing device to sequentially adjust the target flexible tube to multiple preset static limit positions and corresponding multiple static limit postures, and collecting first pose data at each static limit position and corresponding static limit posture; controlling the pose testing device to sequentially move the target flexible tube according to multiple preset trajectories, and collecting second pose data of multiple key points corresponding to each trajectory.

[0007] According to embodiments of this disclosure, the plurality of static limit positions include: a limit extension position of the target flexible tube along a first direction, a limit extension position along a second direction, and a limit extension position along a third direction, relative to the mounting reference point of the target flexible tube on the pose testing device, wherein the first direction, the second direction, and the third direction are orthogonal to each other; the plurality of static limit attitudes include at least two of the following: a limit rotation attitude of the target flexible tube about a first axis, a limit rotation attitude about a second axis, and a limit rotation attitude about a third axis, relative to the initial rotation attitude of the target flexible tube, wherein the first axis, the second axis, and the third axis are orthogonal to each other.

[0008] According to embodiments of this disclosure, the multiple trajectories include at least two of the following: a motion path from a first position to a second position along any one of a first direction, a second direction, and a third direction; and a motion path from a first posture to a second posture around any one of a first axis, a second axis, and a third axis.

[0009] According to embodiments of this disclosure, acquiring first pose data at each static limit position and corresponding static limit attitude includes: scanning the target flexible tube at each static limit position and corresponding static limit attitude to obtain first pose data.

[0010] According to embodiments of this disclosure, the multiple key nodes include at least two of the following: extreme endpoints of the trajectory, velocity change points, and trajectory inflection points; acquiring second pose data for multiple key points corresponding to each trajectory includes: acquiring three-dimensional data for each key node obtained by scanning while the target flexible tube is sequentially adjusted to each key node and kept stationary; and stitching together the three-dimensional data of each key node to obtain second pose data.

[0011] According to embodiments of this disclosure, adjusting initial parameters based on multiple first pose data and multiple second pose data to obtain target parameters for a train flexible tube simulation model includes: iteratively executing adjustment operations based on multiple first pose data and multiple second pose data to adjust initial parameters until a preset iteration condition is reached, and then outputting the target parameters.

[0012] According to an embodiment of this disclosure, the (K+1)th adjustment operation includes: training an initial simulation model based on the Kth set of model parameters obtained from the Kth adjustment operation to obtain the initial simulation model after the Kth training; acquiring the Kth set of simulation data for the target flexible tube output by the initial simulation model after the Kth training; comparing the static simulation data in the Kth set of simulation data with multiple first pose data to obtain a first deviation value of the static simulation data compared to the multiple first pose data; comparing the dynamic simulation data in the Kth set of simulation data with multiple second pose data to obtain a second deviation value of the dynamic simulation data compared to the multiple second pose data; and, if the first deviation value and the second deviation value do not meet the preset data conditions, performing the (K+1)th adjustment on the initial parameters to obtain the (K+1)th set of model parameters.

[0013] According to embodiments of this disclosure, the preset iteration conditions include: the first deviation value and the second deviation value satisfy preset data conditions, and / or reach a preset number of iterations.

[0014] According to embodiments of this disclosure, the preset installation constraints include at least one of the following: the installation location of the target flexible tube on the train, the installation method, installation boundary restrictions, and train structure restrictions.

[0015] Another aspect of this disclosure provides a device for determining the installation information of a train flexible tube, comprising: an output module, which outputs target simulation data corresponding to the target flexible tube using a train flexible tube simulation model; a determination module, which determines the installation information of the target flexible tube on the train based on the target simulation data, wherein the train flexible tube simulation model is determined by target parameters; a fixing module, which fixes the target flexible tube to a posture testing device according to preset installation constraints; a first acquisition module, which acquires multiple first posture data and multiple second posture data of the target flexible tube collected by the posture testing device, wherein the multiple first posture data are used to simulate the static limit position and static limit attitude of the target flexible tube when the train is stationary, and the multiple second posture data are used to simulate the maximum range of motion of the target flexible tube when the train is running; a second acquisition module, which acquires the initial parameters of the train flexible tube simulation model for the target flexible tube; and an adjustment module, which adjusts the initial parameters based on the multiple first posture data and multiple second posture data to obtain the target parameters of the train flexible tube simulation model.

[0016] Another aspect of this disclosure provides an electronic device comprising:

[0017] One or more processors;

[0018] Memory, used to store one or more programs.

[0019] Specifically, when one or more programs are executed by one or more processors, the one or more processors implement the above method.

[0020] Another aspect of this application provides a train including the aforementioned electronic equipment.

[0021] Another aspect of this disclosure provides a computer-readable storage medium storing computer-executable instructions that, when executed, are used to implement the methods described above.

[0022] Another aspect of this disclosure provides a computer program product including computer-executable instructions that, when executed, are used to implement the methods described above. Attached Figure Description

[0023] The above and other objects, features and advantages of this disclosure will become clearer from the following description of embodiments with reference to the accompanying drawings, in which:

[0024] Figure 1 The illustration schematically presents an exemplary system architecture for determining train flexible tube installation information, including methods, apparatus, electronic devices, trains, storage media, and program products to which the present disclosure can be applied;

[0025] Figure 2 A flowchart illustrating a method for determining train flexible tube installation information according to an embodiment of the present disclosure is shown schematically.

[0026] Figure 3 A flowchart illustrating a method for determining train flexible tube installation information according to another embodiment of the present disclosure is shown schematically.

[0027] Figure 4 A flowchart illustrating a method for determining train flexible tube installation information according to another embodiment of the present disclosure is shown schematically.

[0028] Figure 5 A schematic diagram of a target flexible tube under static operating conditions according to an embodiment of the present disclosure is shown.

[0029] Figure 6 A schematic diagram illustrating the scanning results of a target flexible tube under static conditions according to an embodiment of the present disclosure is shown.

[0030] Figure 7 This diagram illustrates the scanning results of a target flexible tube under dynamic operating conditions according to an embodiment of the present disclosure.

[0031] Figure 8 The diagram illustrates the simulation results of the target flexible tube under static operating conditions according to an embodiment of the present disclosure.

[0032] Figure 9A diagram illustrating a comparison between static simulation data and first pose data according to an embodiment of the present disclosure is shown.

[0033] Figure 10 A diagram illustrating a comparison between static simulation data and first pose data according to another embodiment of this disclosure is shown.

[0034] Figure 11 A schematic diagram illustrating the scanning results of a target flexible tube under dynamic operating conditions according to another embodiment of the present disclosure is shown.

[0035] Figure 12 The diagram illustrates the simulation results of the target flexible tube under dynamic operating conditions according to an embodiment of the present disclosure.

[0036] Figure 13 A diagram illustrating a comparison between dynamic simulation data and second pose data according to an embodiment of the present disclosure is shown.

[0037] Figure 14 A block diagram schematically illustrates a device for determining train flexible tube installation information according to an embodiment of the present disclosure; and

[0038] Figure 15 A block diagram of an electronic device suitable for a method of determining train flexible tube installation information according to an embodiment of the present disclosure is shown schematically. Detailed Implementation

[0039] The embodiments of the present disclosure will now be described with reference to the accompanying drawings. However, it should be understood that these descriptions are exemplary only and are not intended to limit the scope of the disclosure. In the following detailed description, numerous specific details are set forth to provide a thorough understanding of the embodiments of the present disclosure for ease of explanation. However, it will be apparent that one or more embodiments may be practiced without these specific details. Furthermore, descriptions of well-known structures and techniques are omitted in the following description to avoid unnecessarily obscuring the concepts of the present disclosure.

[0040] The terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit this disclosure. The terms “comprising,” “including,” etc., as used herein indicate the presence of features, steps, operations, and / or components, but do not exclude the presence or addition of one or more other features, steps, operations, or components.

[0041] All terms used herein (including technical and scientific terms) have the meanings commonly understood by those skilled in the art, unless otherwise defined. It should be noted that the terms used herein are to be interpreted in a manner consistent with the context of this specification, and not in an idealized or overly rigid way.

[0042] When using expressions such as "at least one of A, B and C", they should generally be interpreted in accordance with the meaning that is commonly understood by those skilled in the art (e.g., "a system having at least one of A, B and C" should include, but is not limited to, a system having A alone, a system having B alone, a system having C alone, a system having A and B, a system having A and C, a system having B and C, and / or a system having A, B and C, etc.).

[0043] In the embodiments disclosed herein, the collection, updating, analysis, processing, use, transmission, provision, disclosure, and storage of data (e.g., including but not limited to user personal information) comply with relevant laws and regulations, are used for legitimate purposes, and do not violate public order and good morals. In particular, necessary measures have been taken to prevent unauthorized access to user personal information data and to safeguard user personal information security, network security, and national security.

[0044] In the embodiments disclosed herein, user authorization or consent is obtained before acquiring or collecting user personal information.

[0045] Flexible tubes (such as cables) are an important component of high-speed trains. The length, dimensions, stiffness, and bending radius of the flexible tube are key factors that constrain its spatial posture. For example, if the flexible tube is too short, it will be taut when the train is stationary, while if it is too long, it will sag excessively when the train is stationary.

[0046] The relevant methods typically involve designers relying on their experience during the early design phase. For example, designers use their experience with similar models and theoretical estimations to determine the fixed points, wiring paths, and allowable lengths for the flexible tube installation. Furthermore, these methods are usually validated during the vehicle production phase to ensure the design is reasonable. For instance, after the train enters the car body assembly stage and the flexible tube is actually installed, manual on-site verification is performed to check the spatial orientation of the flexible tube. This includes visually observing the sag and stretch of the flexible tube when it is stationary, and manually pushing car body components (such as bogies) to simulate operating conditions and check whether the flexible tube rubs against or pulls against surrounding components.

[0047] However, in the relevant methods, on the one hand, experience is difficult to cover the differences between different vehicle models and different flexible tube specifications. On the other hand, the vehicle body is basically formed in the production stage. If the flexible tube needs to be modified, it will involve the modification of multiple parts. For example, adjusting the fixing point requires re-drilling holes, and changing the installation path of the flexible tube requires the removal of existing parts. Therefore, the cost is extremely high, and multiple departments need to work together, resulting in low work efficiency.

[0048] In view of this, embodiments of the present disclosure provide a method for determining the installation information of a train flexible tube, comprising: for a target flexible tube to be installed on a train, outputting target simulation data corresponding to the target flexible tube using a train flexible tube simulation model; determining the installation information of the target flexible tube on the train based on the target simulation data, wherein the train flexible tube simulation model is determined by target parameters, and determining the target parameters of the train flexible tube simulation model includes: fixing the target flexible tube to a posture testing device according to preset installation constraints; acquiring multiple first posture data and multiple second posture data of the target flexible tube collected by the posture testing device, wherein the multiple first posture data are used to simulate the static limit position and static limit attitude of the target flexible tube when the train is stationary, and the multiple second posture data are used to simulate the maximum range of motion of the target flexible tube when the train is running; acquiring the initial parameters of the train flexible tube simulation model for the target flexible tube; adjusting the initial parameters based on the multiple first posture data and multiple second posture data to obtain the target parameters of the train flexible tube simulation model.

[0049] Figure 1 An exemplary system architecture 100 is schematically illustrated, comprising methods, apparatus, electronic devices, trains, storage media, and program products for determining train flexible tube installation information to which the present disclosure can be applied. It should be noted that... Figure 1 The examples shown are merely examples of system architectures that can be applied to the embodiments of this disclosure, in order to help those skilled in the art understand the technical content of this disclosure, but do not mean that the embodiments of this disclosure cannot be used in other devices, systems, environments or scenarios.

[0050] like Figure 1 As shown, the system architecture 100 according to this embodiment may include a train 101, a network 102, and a server 103. The network 104 serves as a medium for providing a communication link between the train 101 and the server 103. The network 104 may include various connection types, such as wired and / or wireless communication links, etc.

[0051] It should be noted that the method for determining the installation information of the train flexible tube provided in this application embodiment can generally be executed by the server 105. Accordingly, the system for determining the installation information of the train flexible tube provided in this application embodiment can generally be set in the server 105.

[0052] For example, for a target flexible tube to be installed on train 101, server 105 can execute a method for determining the installation information of the train flexible tube, including: for the target flexible tube to be installed on the train, using a train flexible tube simulation model to output target simulation data corresponding to the target flexible tube; determining the installation information of the target flexible tube on the train based on the target simulation data, wherein the train flexible tube simulation model is determined by target parameters, and determining the target parameters of the train flexible tube simulation model includes: fixing the target flexible tube to the posture test equipment according to preset installation constraints; acquiring multiple first posture data and multiple second posture data of the target flexible tube collected by the posture test equipment, wherein the multiple first posture data are used to simulate the static limit position and static limit attitude of the target flexible tube when the train is stationary, and the multiple second posture data are used to simulate the maximum range of motion of the target flexible tube when the train is running; acquiring the initial parameters of the train flexible tube simulation model for the target flexible tube; adjusting the initial parameters based on the multiple first posture data and multiple second posture data to obtain the target parameters of the train flexible tube simulation model.

[0053] Figure 2 A flowchart illustrating a method for determining train flexible tube installation information according to an embodiment of the present disclosure is shown.

[0054] like Figure 2 As shown, the method includes operations S210~S220.

[0055] When operating S210, for the target flexible tube to be installed on the train, the train flexible tube simulation model is used to output the target simulation data corresponding to the target flexible tube.

[0056] During the S220 operation, the installation information of the target flexible tube on the train is determined based on the target simulation data.

[0057] For example, a train flexible tube simulation model can be built to simulate the spatial attitude of the flexible tube when the train is stationary and in motion, thus obtaining target simulation data. The reserved length of the flexible tube can be adjusted based on the target simulation data to avoid it breaking easily if too long or collapsing if too short. The spacing between fixing points can also be adjusted based on the target simulation data. For example, the flexible tube can include cables, hoses, etc.

[0058] By using the train flexible tube simulation model to output target simulation data corresponding to the target flexible tube, and determining the installation information of the target flexible tube on the train based on the target simulation data, the spatial orientation of the flexible tube can be accurately determined in the design stage. There is no need to actually manufacture and install the flexible tube. The attitude of the flexible tube under various working conditions can be simulated, reducing the material and time costs of physical testing, avoiding the problem of large-scale modifications required in the subsequent production and processing stages, and improving the installation efficiency of the flexible tube.

[0059] According to embodiments of this disclosure, the train flexible tube simulation model is determined by target parameters. To improve the accuracy of the train flexible tube simulation model in simulating the spatial attitude of the flexible tube when the train is stationary and in motion, it is necessary to accurately determine the target parameters of the train flexible tube simulation model.

[0060] Figure 3 A flowchart illustrating a method for determining train flexible tube installation information according to another embodiment of the present disclosure is shown.

[0061] like Figure 3 As shown, the method includes operations S310~S340.

[0062] When operating S310, the target flexible tube is fixed to the posture test equipment according to the preset installation constraints.

[0063] For example, by fixing the target flexible tube to the posture testing equipment according to preset installation constraints, the actual installation layout of the target flexible tube on a train can be simulated. For instance, if the preset actual installation layout includes a fixing point spacing of 0.5m for the flexible tube, then the target flexible tube can be installed on the posture testing equipment with a fixing point spacing of 0.5m. The posture testing equipment may include a test bench, such as a test bench capable of performing six degrees of freedom motion (3 translational degrees of freedom and 3 rotational degrees of freedom) of the flexible tube in space.

[0064] During operation S320, multiple first pose data and multiple second pose data of the target flexible tube are acquired by the pose testing equipment. The multiple first pose data are used to simulate the static limit position and static limit attitude of the target flexible tube when the train is stationary, and the multiple second pose data are used to simulate the maximum range of motion of the target flexible tube when the train is running.

[0065] For example, the first pose data can correspond to the pose data of the target flexible tube under static working conditions, such as the initial pose of the target flexible tube in a static state, the position and attitude of the target flexible tube after being stretched to the maximum along the longitudinal direction of the train and then in a static state. The initial pose, for example, includes the spatial attitude of the target flexible tube in a static state without external force active stretching or contraction after it is fixed to the pose test equipment according to preset installation constraints.

[0066] The second pose data can correspond to the pose data of the target flexible tube under dynamic working conditions, such as the pose of the target flexible tube during the process of stretching to the limit and shrinking to the limit along the longitudinal direction of the train.

[0067] In operation S330, the initial parameters of the train flexible tube simulation model for the target flexible tube are obtained.

[0068] For example, the initial parameters of the train flexible tube simulation model can be determined based on the first pose data. For instance, at least two of the following can be extracted from the first pose data: the installation reference point coordinates, the extreme position coordinates, and the static extreme attitude geometric parameters of the target flexible tube.

[0069] In operation S340, the initial parameters are adjusted based on multiple first pose data and multiple second pose data to obtain the target parameters of the train flexible tube simulation model.

[0070] For example, since the multiple first pose data and multiple second pose data are obtained by reproducing the actual installation constraints of the train on the pose test equipment, they are more in line with the actual working conditions of the train. Moreover, they are obtained through physical tests rather than determined by experience, so there is no human subjective judgment and the accuracy is high.

[0071] The initial parameters are uncalibrated and may deviate from the actual installation scenario. Therefore, the initial parameters can be adjusted based on multiple first pose data and multiple second pose data to obtain more accurate target parameters. This allows for the accurate construction of a train flexible tube simulation model, enabling the model to accurately reproduce the real spatial posture of the flexible tube and thus determine the optimal installation information.

[0072] According to embodiments of this disclosure, by acquiring multiple first pose data and multiple second pose data of the target flexible tube collected by a pose testing device, adjusting initial parameters based on the multiple first pose data and multiple second pose data, the target parameters of the train flexible tube simulation model are obtained. The train flexible tube simulation model outputs target simulation data corresponding to the target flexible tube, thereby determining the installation information of the target flexible tube on the train based on the target simulation data. This accurately determines the model parameters, enabling the train flexible tube simulation model to precisely reproduce the true spatial posture of the flexible tube. Furthermore, it allows for accurate judgment and verification of the flexible tube's spatial posture during the design phase. Compared to related methods that only verify during vehicle production, this eliminates the need for actual vehicle manufacturing and installation of the flexible tube on the train. Modifying the flexible tube installation scheme does not require modifications to multiple components, reducing modification costs and improving installation efficiency.

[0073] According to embodiments of this disclosure, the preset installation constraints include at least one of the following: the installation location of the target flexible tube on the train, the installation method, installation boundary restrictions, and train structure restrictions.

[0074] For example, regarding the installation location, two main fixing points for installing the target flexible tube can be set on the tooling frame of the posture testing equipment according to the actual installation coordinates of the target flexible tube on the train. The spatial height and horizontal distance between the two main fixing points correspond to the actual installation coordinates of the target flexible tube on the train.

[0075] For example, regarding the installation method, if the target flexible tube is fixed on the train by a snap-fit ​​clamp, then the target flexible tube can be fixed on the posture test equipment by the snap-fit ​​clamp.

[0076] For example, installation boundary constraints may include: if the maximum length of the target flexible tube on the train is 1 meter, then the maximum length of the target flexible tube on the posture test equipment is also 1 meter; train structure constraints may include: referencing the height limit of the equipment compartment of the train body (such as a net height of 200 mm inside the compartment), the vertical space of the test equipment is limited to 200 mm to ensure that the vertical swing height of the flexible tube does not exceed this limit, thereby replicating the spatial structure constraints of the train equipment compartment.

[0077] According to embodiments of this disclosure, by fixing the target flexible tube to the posture test equipment according to preset installation constraints, the test scenario can accurately simulate the actual installation conditions of the train, thereby ensuring that the collected posture data is accurate and usable.

[0078] Figure 4 A flowchart illustrating a method for determining train flexible tube installation information according to another embodiment of the present disclosure is shown.

[0079] According to embodiments of this disclosure, acquiring multiple first pose data and multiple second pose data of a target flexible tube collected by a pose testing device includes: controlling the pose testing device to sequentially adjust the target flexible tube to multiple preset static limit positions and corresponding multiple static limit postures, and collecting first pose data at each static limit position and corresponding static limit posture; controlling the pose testing device to sequentially move the target flexible tube according to multiple preset trajectories, and collecting second pose data of multiple key points corresponding to each trajectory.

[0080] like Figure 4 As shown, operating conditions and flexible tube parameters can be set. Operating conditions include static and dynamic operating conditions, while flexible tube parameters include multiple static limit positions and corresponding static limit attitudes. Experiments can be conducted based on the operating conditions and flexible tube parameters. Experiments may include acquiring first pose data for each static limit position and corresponding static limit attitude, and acquiring second pose data for multiple key points.

[0081] Figure 5 A schematic diagram of a target flexible tube under static operating conditions according to an embodiment of the present disclosure is shown.

[0082] For example, for the static working condition of the target flexible tube, the posture testing equipment can be controlled to adjust the state of the flexible tube. For example, by using the clamps, displacement drives, angle drives, etc. of the posture testing equipment, the target flexible tube can be sequentially adjusted to a number of preset static limit positions and corresponding static limit postures, such as adjusting it to the position where it is stretched to the maximum along the first direction, or adjusting it to the posture where it is rotated to the maximum angle along the first axis.

[0083] For example, for the dynamic working conditions of the target flexible tube, the pose test equipment can be controlled to make the target flexible tube move along the trajectory. The maximum contour range of all the space occupied by the target flexible tube during the movement can be determined by the second pose data. For example, the envelope of the target flexible tube when it moves along the trajectory can be determined.

[0084] According to embodiments of this disclosure, by controlling the pose testing equipment to sequentially adjust the target flexible tube to a plurality of preset static limit positions and corresponding plurality of static limit postures, and by controlling the pose testing equipment to move the target flexible tube sequentially along a plurality of preset trajectories, it is possible to comprehensively collect various pose data of the target flexible tube under static and dynamic working conditions, thereby comprehensively covering various poses under actual working conditions, and thus accurately calibrating the simulation model parameters.

[0085] According to embodiments of this disclosure, the plurality of static limit positions include: a limit extension position of the target flexible tube along a first direction, a limit extension position along a second direction, and a limit extension position along a third direction, relative to the mounting reference point of the target flexible tube on the posture testing equipment, wherein the first direction, the second direction, and the third direction are orthogonal to each other.

[0086] For example, the mounting reference point may include any fixed point of the target flexible tube on the posture testing equipment. The first direction is, for example, the x-axis direction (such as the longitudinal direction of a train, i.e., the direction from the front to the rear of the train), the second direction is, for example, the y-axis direction (such as the transverse direction of a train, i.e., the direction from the left side to the right side of the train), and the third direction is, for example, the z-axis direction (such as the transverse direction of a train, i.e., the direction from the left side to the right side of the train).

[0087] The ultimate extension position of the target flexible tube along the first direction may include the position of the target flexible tube when stretched to its length limit along the positive x-axis and the position of the target flexible tube when contracted to its limit along the negative x-axis; the ultimate extension position of the target flexible tube along the second direction may include the position of the target flexible tube when swinging to its length limit along the positive y-axis and the position of the target flexible tube when swinging to its length limit along the negative y-axis; the ultimate extension position of the target flexible tube along the third direction may include the position of the target flexible tube when raised to its length limit along the positive z-axis and the position of the target flexible tube when raised to its length limit along the negative z-axis.

[0088] According to embodiments of this disclosure, the plurality of static extreme postures include at least two of the following: extreme rotational postures of the target flexible tube about a first axis, extreme rotational postures about a second axis, and extreme rotational postures about a third axis, relative to the initial rotational posture of the target flexible tube, wherein the first axis, the second axis, and the third axis are orthogonal to each other.

[0089] For example, the first axis may include the aforementioned x-axis, the second axis may include the aforementioned y-axis, and the third axis may include the aforementioned z-axis. The limiting rotational posture of the target flexible tube about the first axis may include the posture when the flexible tube rotates about the positive and / or negative x-axis, reaching a physical limit or installation constraint limit; correspondingly, the limiting rotational posture of the target flexible tube about the second axis may include the posture when the flexible tube rotates about the positive and / or negative y-axis, reaching a physical limit or installation constraint limit; the limiting rotational posture of the target flexible tube about the third axis may include the posture when the flexible tube rotates about the positive and / or negative z-axis, reaching a physical limit or installation constraint limit, wherein the physical limit may include the target flexible tube twisting to a critical angle at which core wire damage is imminent; the installation constraint limit may include the target flexible tube being unable to continue positive twisting due to the limitation of the fixing clamp. For example, the x, y, and z directions may follow the right-hand rule.

[0090] According to embodiments of this disclosure, the multiple trajectories include at least two of the following: a motion path from a first position to a second position along any one of a first direction, a second direction, and a third direction; and a motion path from a first posture to a second posture around any one of a first axis, a second axis, and a third axis.

[0091] For example, the first position and the second position may include two opposite extreme positions in the same direction. For example, the trajectory may include a motion path from x maximum to x minimum along the x-axis direction, and correspondingly, it may also include a motion path from y maximum to y minimum along the y-axis direction and a motion path from z maximum to z minimum along the z-axis direction.

[0092] For example, the first and second poses can include two opposite extreme rotational poses on the same rotation axis. For instance, they can include poses reaching the positive torsional limit (e.g., maximum Rx) and the reverse torsional line (e.g., minimum Rx) along the first axis (e.g., denoted as Rx). The trajectory can include the motion path of the target flexible tube from maximum Rx to minimum Rx, from maximum Ry to minimum Ry, from maximum Rz to minimum Rz, etc. Correspondingly, the second pose data can include the envelope from maximum x to minimum x, the envelope from maximum y to minimum y, the envelope from maximum z to minimum z, the envelope from maximum Rx to minimum Rx, the envelope from maximum Ry to minimum Ry, and the envelope from maximum Rz to minimum Rz.

[0093] According to embodiments of this disclosure, by using multiple static extreme positions and multiple trajectories, the position and attitude data of the target flexible tube under various working conditions can be collected comprehensively and accurately, thereby improving the accuracy of simulation parameter calibration.

[0094] According to embodiments of this disclosure, acquiring first pose data at each extreme position and corresponding static extreme attitude includes: scanning the target flexible tube at each extreme position and corresponding static extreme attitude to obtain first pose data.

[0095] For example, the target flexible tube can be scanned under both static and dynamic operating conditions, such as... Figure 4 As shown, 3D scanning can be performed and the scan results can be checked, for example, by using a 3D scanner. The spatial orientation of the target flexible tube can be obtained using a 3D scanner and output as a mesh file.

[0096] like Figure 4 As shown, it can be determined whether the scan results are suitable, such as determining the data accuracy of the scan results (e.g., whether the scan error is less than the preset error threshold) and the data integrity of the scan data (e.g., whether it covers all static limit states). If it is unsuitable (e.g., poor data accuracy, incomplete data, etc.), a 3D scan needs to be performed again.

[0097] Figure 6 The diagram illustrates the scanning results of a target flexible tube under static conditions according to an embodiment of the present disclosure.

[0098] Figure 7 The diagram illustrates the scanning results of a target flexible tube under dynamic operating conditions according to an embodiment of the present disclosure.

[0099] Scanning can determine the true geometric characteristics of a target flexible tube under static conditions, such as bending curvature, torsion angle, and spatial coordinate distribution, as well as its true geometric characteristics under motion conditions, such as bending deformation at trajectory inflection points. For example, cables can be scanned.

[0100] For example, the scanning conditions for scanning the target flexible tube under static conditions can be completely consistent with the static conditions referenced in the construction of the simulation model. Similarly, the scanning conditions for scanning the target flexible tube under dynamic conditions can be completely consistent with the dynamic conditions referenced in the construction of the simulation model. For instance, the installation constraints are consistent (such as the installation reference point, fixing method, and tension of the flexible tube on the posture test equipment are completely consistent), and the settings of the dynamic and static conditions are completely consistent (such as the trajectories both including a motion path along the x-axis from the maximum to the minimum x). By setting the same conditions, the test data and scanning data can be accurately aligned, and the initial parameters can be adjusted based on the first and second posture data.

[0101] For example, the amount of scanned data may be large. Key parameters such as the coordinates of the installation reference point, the coordinates of the extreme positions, and the static extreme attitude geometric parameters can be used as the basis for constructing a simulation model of the train flexible tube. The coordinates of the installation reference point can include the three-dimensional spatial coordinates of a fixed reference point on the posture testing equipment. This fixed reference point may include, for example, the clamping center of the fixture, the positioning pin connection point between the target flexible tube and the posture testing equipment, etc. The extreme position coordinates can include, but are not limited to, the coordinates of the end point when the target flexible tube is stretched to its maximum and minimum x-axis, but can also include the coordinates of the end point when y-axis is maximized, y-minimum, z-maximum, and z-minimum. The static extreme attitude geometric parameters include, for example, the torsion angle and bending radius when the target flexible tube reaches its maximum or minimum Rx, Ry, and Rz.

[0102] According to embodiments of this disclosure, scanning technology can convert the test posture into a model form so that it can be compared with simulation results. By setting the same working conditions to complete the test and scanning, it can be ensured that the pose data and initial parameters can be accurately compared, so that the initial parameters can be adjusted based on multiple first pose data and multiple second pose data.

[0103] For example, since the scanner can only scan static physical objects, a step-by-step scanning method can be used to obtain the second scan data obtained by scanning the target flexible tube while it is in motion.

[0104] According to embodiments of this disclosure, multiple key nodes include at least two of the following: extreme endpoints of the trajectory, points of sudden velocity changes, and trajectory inflection points.

[0105] According to embodiments of this disclosure, collecting second pose data for multiple key points corresponding to each trajectory includes:

[0106] Acquire the 3D data of each key node obtained by scanning while the target flexible tube is sequentially adjusted to each key node and kept stationary;

[0107] The 3D data of each key node are stitched together to obtain the second pose data.

[0108] For example, the extreme endpoints of the trajectory may include the starting point and ending point of the trajectory, such as the position where x is maximum and x is minimum; the velocity change point may include the position where the velocity of the target flexible tube changes abruptly, such as the starting point of the acceleration segment of the trajectory and the ending point of the deceleration segment; the trajectory inflection point may include the position where the direction of motion of the target flexible tube changes, such as the turning point of the translational trajectory and the attitude switching point of the rotational trajectory.

[0109] For example, for any key point, the pose testing equipment can be controlled to drive the target flexible tube to move along a preset trajectory to the reference node, pause and keep it stationary, and then perform a three-dimensional scan on the stationary flexible tube to obtain the geometric shape data of the node, thereby obtaining the three-dimensional data for the key node.

[0110] For example, the three-dimensional data of each key node can be stitched together based on the order of each reference node in the preset dynamic trajectory to obtain the second pose data. For example, the stitching can be done by coordinate registration algorithm (such as ICP algorithm) or other methods. The stitching method of the three-dimensional data of each key node is not limited here.

[0111] According to the embodiments of this disclosure, by determining multiple reference nodes passed by the target flexible tube when it moves along a preset dynamic trajectory, the three-dimensional data of each key node obtained by scanning when the target flexible tube is sequentially adjusted to each key node and kept stationary is obtained, and the three-dimensional data of each key node is stitched together. The second pose data can be accurately obtained by step-by-step scanning, which solves the problem that the scanner can only scan static objects and cannot obtain the pose data of the target flexible tube during its movement.

[0112] According to embodiments of this disclosure, adjusting initial parameters based on multiple first pose data and multiple second pose data to obtain target parameters for a train flexible tube simulation model includes: iteratively executing adjustment operations based on multiple first pose data and multiple second pose data to adjust initial parameters until a preset iteration condition is reached, and then outputting the target parameters.

[0113] like Figure 4 As shown, the target flexible tube can be simulated, such as a cable, and a model can be output. For example, a train flexible tube simulation model can be built based on the simulation parameters. It can be determined whether the model is suitable. For example, it can be determined whether the model conforms to common sense in engineering. If it does not conform to common sense in engineering (i.e., it is not suitable), there is no need to carry out the next step of experimental simulation benchmarking. Instead, the train flexible tube simulation model can be rebuilt.

[0114] like Figure 4 As shown, if the scanning results and the model are suitable, experimental simulation can be performed for comparison. This involves comparing multiple first pose data and multiple second pose data with the initial parameters in the same software to determine the deviations between the multiple first pose data and multiple second pose data and the initial parameters.

[0115] like Figure 4As shown, it can be determined whether the benchmark meets the requirements. For example, if the deviation is large, it means that the initial parameters are not accurate enough, that is, the benchmark does not meet the requirements. Therefore, the initial parameters can be adjusted, such as by revising the initial parameters. Benchmark data can also be recorded, such as the adjustment content and the degree of deviation.

[0116] According to an embodiment of this disclosure, the (K+1)th adjustment operation includes: training an initial simulation model based on the Kth set of model parameters obtained from the Kth adjustment operation to obtain the initial simulation model after the Kth training; acquiring the Kth set of simulation data for the target flexible tube output by the initial simulation model after the Kth training; comparing the static simulation data in the Kth set of simulation data with multiple first pose data to obtain a first deviation value of the static simulation data compared to the multiple first pose data; comparing the dynamic simulation data in the Kth set of simulation data with multiple second pose data to obtain a second deviation value of the dynamic simulation data compared to the multiple second pose data; and, if the first deviation value and the second deviation value do not meet the preset data conditions, performing the (K+1)th adjustment on the initial parameters to obtain the (K+1)th set of model parameters.

[0117] Figure 8 The diagram illustrates the simulation results of the target flexible tube under static operating conditions according to an embodiment of the present disclosure.

[0118] For example, static simulation data may include simulation parameters of the target flexible tube in a static state, while dynamic simulation data may include simulation parameters of the target flexible tube in a moving state. The target flexible tube may be, for example, a cable.

[0119] For each iteration: for example, since both the static simulation data and the first pose data correspond to the same static working condition of the target flexible tube, the static simulation data can be compared with the first pose data. For example, the deviation of the static simulation data from the first pose data can be determined. If the deviation is greater than a preset threshold, it indicates that the initial parameters are not accurate enough. Therefore, the initial parameters can be modified. In the next iteration, the modified initial parameters are compared with the first scan data again, and the deviation is determined.

[0120] For example, it may also include: since both the dynamic simulation data and the second pose data correspond to the same dynamic working conditions of the target flexible tube, the dynamic simulation data can be compared with the second pose data. For example, the deviation of the dynamic simulation data from the second pose data can be determined. If the deviation is greater than a preset threshold, it indicates that the dynamic simulation data is not accurate enough. Therefore, the initial parameters can be modified. In the next iteration operation, the modified initial parameters are compared with the second scan data again to determine the deviation.

[0121] For example, in the first adjustment operation (i.e., K is 0), the initial simulation model can be trained using the initial parameters to obtain the first training completed initial simulation model; the first set of simulation data for the target flexible tube can be obtained from the output of the first training completed initial simulation model; the static simulation data in the first set of simulation data can be compared with multiple first pose data to obtain the first deviation value of the static simulation data compared with multiple first pose data, for example, the deviation is 40%; the dynamic simulation data in the first set of simulation data can also be compared with multiple second pose data to obtain the second deviation value of the dynamic simulation data compared with multiple second pose data, for example, 45%.

[0122] Figure 9 A diagram illustrating a comparison between static simulation data and first pose data according to an embodiment of the present disclosure is shown.

[0123] Depend on Figure 9 It can be seen that, for example, for static working conditions, the deviation of static simulation data from the first pose data is relatively large. Figure 9 (The two flexible tubes in the middle do not overlap), that is, the first deviation value does not meet the preset data conditions. For example, the preset thresholds corresponding to the first deviation value and the second deviation value are both 20%. In the first adjustment operation, since the first deviation value is greater than the preset threshold, the initial parameters can be adjusted for the first time to obtain the second set of model parameters (the first set is, for example, the initial parameters). Therefore, the initial parameters can be adjusted and the second adjustment operation can be performed.

[0124] Figure 10 A diagram illustrating a comparison between static simulation data and first pose data according to another embodiment of the present disclosure is shown.

[0125] Depend on Figure 10 It can be seen that, for example, for static working conditions, the deviation of static simulation data from the first pose data is relatively small. Figure 10 (The two flexible tubes in the middle are basically overlapping), that is, the first deviation value meets the preset data conditions, so the iteration can be stopped and the target parameters can be output.

[0126] Figure 11 A schematic diagram illustrating the scanning results of a target flexible tube under dynamic operating conditions according to another embodiment of the present disclosure is shown. Figure 12 The diagram illustrates the simulation results of the target flexible tube under dynamic operating conditions according to an embodiment of the present disclosure. Figure 13 A diagram illustrating a comparison between dynamic simulation data and second pose data according to an embodiment of the present disclosure is shown.

[0127] Depend on Figures 11-13 It can be seen that the deviation of the dynamic simulation data from the second pose data is relatively small. Figure 13(Since the two flexible tubes have significantly different shapes, the initial parameters need to be adjusted again.)

[0128] According to embodiments of this disclosure, simulation model parameters can be continuously corrected through iterative adjustment operations, thereby outputting more accurate target parameters.

[0129] According to embodiments of this disclosure, the preset iteration conditions include: the first deviation value and the second deviation value satisfy preset data conditions, and / or reach a preset number of iterations.

[0130] For example, meeting the preset data conditions may include a first deviation value and / or a second deviation value being less than a preset threshold. The preset thresholds corresponding to the first deviation value and the second deviation value may be the same or different, and can be set according to actual needs. The value of the preset threshold can also be set according to actual needs, and is not limited here.

[0131] For example, the preset condition could be reaching a preset number of iterations, such as 1000 iterations. After the number of adjustment operations reaches 1000, the iteration operation can be stopped and the target parameter can be output.

[0132] Figure 14 A block diagram of a device for determining train flexible tube installation information according to an embodiment of the present disclosure is shown schematically.

[0133] like Figure 14 As shown, the train flexible tube installation information determination device 1400 includes the following modules.

[0134] The output module 1401 includes a train flexible tube simulation model that outputs target simulation data corresponding to the target flexible tube.

[0135] The determination module 1402 includes determining the installation information of the target flexible tube on the train based on the target simulation data, wherein the train flexible tube simulation model is determined by the target parameters;

[0136] The fixing module 1403 is used to fix the target flexible tube to the posture test equipment according to the preset installation constraints.

[0137] The first acquisition module 1404 is used to acquire multiple first pose data and multiple second pose data of the target flexible tube collected by the pose test equipment. The multiple first pose data are used to simulate the static limit position and static limit attitude of the target flexible tube when the train is stationary, and the multiple second pose data are used to simulate the maximum range of motion of the target flexible tube when the train is running.

[0138] The second acquisition module 1405 is used to acquire the initial parameters of the train flexible tube simulation model for the target flexible tube;

[0139] The adjustment module 1406 is used to adjust the initial parameters based on multiple first pose data and multiple second pose data to obtain the target parameters of the train flexible tube simulation model.

[0140] The first acquisition module includes a first control submodule and a second control submodule. The first control submodule is used to control the pose testing equipment to sequentially adjust the target flexible tube to a plurality of preset static limit positions and corresponding plurality of static limit postures, and to collect first pose data at each static limit position and corresponding static limit posture. The second control submodule is used to control the pose testing equipment to move the target flexible tube sequentially according to a plurality of preset trajectories, and to collect second pose data of a plurality of key points corresponding to each trajectory.

[0141] The first control submodule includes a first scanning unit, which is used to scan the target flexible tube at each static limit position and the corresponding static limit attitude to obtain the first pose data.

[0142] The second control submodule includes a second scanning unit and a stitching unit. The second scanning unit is used to acquire the three-dimensional data of each key node obtained by scanning when the target flexible tube is sequentially adjusted to each key node and kept stationary. The stitching unit is used to stitch the three-dimensional data of each key node to obtain the second pose data.

[0143] The adjustment module includes an iterative submodule, which iteratively executes adjustments to the initial parameters based on multiple first pose data and multiple second pose data until a preset iteration condition is met, at which point the target parameters are output. The (K+1)th adjustment operation includes: training an initial simulation model based on the Kth set of model parameters obtained from the Kth adjustment operation, resulting in the Kth training-completed initial simulation model; acquiring the Kth set of simulation data for the target flexible tube output by the Kth training-completed initial simulation model; comparing the static simulation data in the Kth set of simulation data with the multiple first pose data to obtain a first deviation value; comparing the dynamic simulation data in the Kth set of simulation data with the multiple second pose data to obtain a second deviation value; and if the first and second deviation values ​​do not meet the preset data conditions, performing the (K+1)th adjustment to the initial parameters to obtain the (K+1)th set of model parameters.

[0144] Any one or more of the modules, submodules, units, and subunits according to embodiments of the present disclosure, or at least part of the functions of any one or more of them, can be implemented in one module. Any one or more of the modules, submodules, units, and subunits according to embodiments of the present disclosure can be implemented by dividing them into multiple modules. Any one or more of the modules, submodules, units, and subunits according to embodiments of the present disclosure can be at least partially implemented as hardware circuitry, such as a Field-Programmable Gate Array (FPGA), a Programmable Logic Array (PLA), a System-on-Chip, a System-on-a-Substrate, a System-on-Package, an Application-Specific Integrated Circuit (ASIC), or implemented in hardware or firmware by any other reasonable means of integrating or packaging circuitry, or implemented in software, hardware, or firmware, or in any suitable combination of any of these three implementation methods. Alternatively, one or more of the modules, submodules, units, and subunits according to embodiments of the present disclosure can be at least partially implemented as computer program modules, which, when run, can perform corresponding functions.

[0145] For example, any and more of the output module 1401, determining module 1402, fixing module 1403, first acquisition module 1404, second acquisition module 1405, and adjustment module 1406 can be combined into one module / unit / subunit, or any one of these modules / units / subunits can be split into multiple modules / units / subunits. Alternatively, at least some of the functions of one or more of these modules / units / subunits can be combined with at least some of the functions of other modules / units / subunits and implemented in one module / unit / subunit. According to embodiments of this disclosure, at least one of the output module 1401, determining module 1402, fixing module 1403, first acquisition module 1404, second acquisition module 1405, and adjustment module 1406 can be at least partially implemented as hardware circuits, such as field-programmable gate arrays (FPGAs), programmable logic arrays (PLAs), systems-on-a-chip, systems-on-a-substrate, systems-on-package, application-specific integrated circuits (ASICs), or any other reasonable means of integrating or packaging circuits, or implemented in software, hardware, or firmware, or in any suitable combination of any of these three implementation methods. Alternatively, at least one of the output module 1401, determining module 1402, fixing module 1403, first acquisition module 1404, second acquisition module 1405, and adjustment module 1406 can be at least partially implemented as a computer program module, which can perform corresponding functions when the computer program module is run.

[0146] It should be noted that the system part for determining the installation information of the train flexible tube in the embodiments of this disclosure corresponds to the method part for determining the installation information of the train flexible tube in the embodiments of this disclosure. The description of the data processing system part is specifically referred to in the method part for determining the installation information of the train flexible tube, and will not be repeated here.

[0147] Figure 15 A block diagram of an electronic device suitable for a method of determining train flexible tube installation information according to an embodiment of the present disclosure is shown schematically. Figure 15 The electronic device shown is merely an example and should not be construed as limiting the functionality and scope of the embodiments disclosed herein.

[0148] like Figure 15 As shown, an electronic device 1500 according to an embodiment of the present disclosure includes a processor 1501, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 1502 or a program loaded from a storage portion 1508 into a random access memory (RAM) 1503. The processor 1501 may include, for example, a general-purpose microprocessor (e.g., a CPU), an instruction set processor and / or an associated chipset and / or a special-purpose microprocessor (e.g., an application-specific integrated circuit (ASIC)), etc. The processor 1501 may also include onboard memory for caching purposes. The processor 1501 may include a single processing unit or multiple processing units for performing different actions of the method flow according to an embodiment of the present disclosure.

[0149] RAM 1503 stores various programs and data required for the operation of electronic device 1500. Processor 1501, ROM 1502, and RAM 1503 are interconnected via bus 1504. Processor 1501 performs various operations of the method flow according to embodiments of the present disclosure by executing programs in ROM 1502 and / or RAM 1503. It should be noted that programs may also be stored in one or more memories other than ROM 1502 and RAM 1503. Processor 1501 may also perform various operations of the method flow according to embodiments of the present disclosure by executing programs stored in one or more memories.

[0150] According to embodiments of this disclosure, the electronic device 1500 may further include an input / output (I / O) interface 1505, which is also connected to a bus 1504. The electronic device 1500 may also include one or more of the following components connected to the input / output (I / O) interface 1505: an input section 1506 including a keyboard, mouse, etc.; an output section 1507 including a cathode ray tube (CRT), liquid crystal display (LCD), etc., and a speaker, etc.; a storage section 1508 including a hard disk, etc.; and a communication section 1509 including a network interface card such as a LAN card, modem, etc. The communication section 1509 performs communication processing via a network such as the Internet. A drive 1510 is also connected to the input / output (I / O) interface 1505 as needed. A removable medium 1511, such as a disk, optical disk, magneto-optical disk, semiconductor memory, etc., is installed on the drive 1510 as needed so that computer programs read from it can be installed into the storage section 1508 as needed.

[0151] According to embodiments of this disclosure, the method flow according to embodiments of this disclosure can be implemented as a computer software program. For example, embodiments of this disclosure include a computer program product comprising a computer program carried on a computer-readable storage medium, the computer program containing program code for performing the methods shown in the flowchart. In such embodiments, the computer program can be downloaded and installed from a network via communication section 1509, and / or installed from removable medium 1511. When the computer program is executed by processor 1501, it performs the functions defined in the system of embodiments of this disclosure. According to embodiments of this disclosure, the systems, devices, apparatuses, modules, units, etc., described above can be implemented by computer program modules.

[0152] This disclosure also provides a computer-readable storage medium, which may be included in the device / apparatus / system described in the above embodiments; or it may exist independently and not assembled into the device / apparatus / system. The computer-readable storage medium carries one or more programs that, when executed, implement the method according to the embodiments of this disclosure.

[0153] According to embodiments of this disclosure, the computer-readable storage medium can be a non-volatile computer-readable storage medium. Examples include, but are not limited to: portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof. In this disclosure, the computer-readable storage medium can be any tangible medium that contains or stores a program that can be used by or in conjunction with an instruction execution system, apparatus, or device.

[0154] For example, according to embodiments of this disclosure, a computer-readable storage medium may include one or more memories other than the ROM 1502 and / or RAM 1503 described above.

[0155] Embodiments of this disclosure also include a computer program product comprising a computer program containing program code for performing the methods provided in the embodiments of this disclosure. When the computer program product is run on an electronic device, the program code is used to enable the electronic device to implement the method for determining train flexible tube installation information provided in the embodiments of this disclosure.

[0156] When the computer program is executed by the processor 1501, it performs the functions defined in the system / apparatus of this disclosure embodiments. According to embodiments of this disclosure, the systems, apparatuses, modules, units, etc., described above can be implemented by computer program modules.

[0157] In one embodiment, the computer program may rely on a tangible storage medium such as an optical storage device or a magnetic storage device. In another embodiment, the computer program may also be transmitted and distributed in the form of signals over a network medium, and may be downloaded and installed via the communication section 1509, and / or installed from the removable medium 1511. The program code contained in the computer program can be transmitted using any suitable network medium, including but not limited to: wireless, wired, etc., or any suitable combination thereof.

[0158] According to embodiments of this disclosure, program code for executing the computer programs provided in embodiments of this disclosure can be written in any combination of one or more programming languages. Specifically, these computational programs can be implemented using high-level procedural and / or object-oriented programming languages, and / or assembly / machine languages. Programming languages ​​include, but are not limited to, languages ​​such as Java, C++, Python, "C", or similar programming languages. The program code can execute entirely on a user's computing device, partially on a user's device, partially on a remote computing device, or entirely on a remote computing device or server. In cases involving remote computing devices, the remote computing device can be connected to the user's computing device via any type of network, including a local area network (LAN) or a wide area network (WAN), or it can be connected to an external computing device (e.g., via the Internet using an Internet service provider).

[0159] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of the present disclosure. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in a block diagram or flowchart, and combinations of blocks in a block diagram or flowchart, may be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions. Those skilled in the art will understand that the features described in the various embodiments of the present disclosure can be combined and / or combined in various ways, even if such combinations are not explicitly described in the present disclosure. In particular, the features described in the various embodiments of this disclosure may be combined and / or combined in various ways without departing from the spirit and teachings of this disclosure. All such combinations and / or combinations fall within the scope of this disclosure.

[0160] The embodiments of this disclosure have been described above. However, these embodiments are for illustrative purposes only and are not intended to limit the scope of this disclosure. Although various embodiments have been described above, this does not mean that the measures in the various embodiments cannot be used advantageously in combination. Various substitutions and modifications can be made by those skilled in the art without departing from the scope of this disclosure, and all such substitutions and modifications should fall within the scope of this disclosure.

Claims

1. A method for determining the installation information of a train flexible tube, comprising: For the target flexible tube to be installed on the train, the train flexible tube simulation model is used to output target simulation data corresponding to the target flexible tube. The installation information of the target flexible tube on the train is determined based on the target simulation data. The train flexible tube simulation model is determined by target parameters, which include: The target flexible tube is fixed to the posture test equipment according to preset installation constraints; Multiple first pose data and multiple second pose data of the target flexible tube are acquired by the pose testing device. The multiple first pose data are used to simulate the static limit position and static limit attitude of the target flexible tube when the train is stationary. The multiple second pose data are used to simulate the maximum range of motion of the target flexible tube when the train is running. Obtain the initial parameters of the train flexible tube simulation model for the target flexible tube; The initial parameters are adjusted based on the multiple first pose data and the multiple second pose data to obtain the target parameters of the train flexible tube simulation model.

2. The method according to claim 1, wherein, The acquisition of multiple first pose data and multiple second pose data of the target flexible tube collected by the pose testing equipment includes: The pose testing device is controlled to sequentially adjust the target flexible tube to a plurality of preset static limit positions and corresponding plurality of static limit postures, and the first pose data is collected at each of the static limit positions and the corresponding static limit postures; The pose testing device is controlled to move the target flexible tube sequentially along multiple preset trajectories, and the second pose data of multiple key points corresponding to each trajectory are collected.

3. The method according to claim 1, wherein, The plurality of static limit positions include: relative to the mounting reference point of the target flexible tube on the posture test equipment, the limit extension position of the target flexible tube along the first direction, the limit extension position along the second direction, and the limit extension position along the third direction, wherein the first direction, the second direction and the third direction are orthogonal to each other. The plurality of static extreme postures include at least two of the following: extreme rotational postures of the target flexible tube about a first axis, extreme rotational postures about a second axis, and extreme rotational postures about a third axis, relative to the initial rotational posture of the target flexible tube, wherein the first axis, the second axis, and the third axis are orthogonal to each other.

4. The method according to claim 3, wherein, The plurality of trajectories includes at least two of the following: a motion path from a first position to a second position along any one of the first direction, the second direction, and the third direction; and a motion path from a first posture to a second posture around any one of the first axis, the second axis, and the third axis.

5. The method according to claim 2, wherein, The step of acquiring the first pose data at each of the static limit positions and the corresponding static limit poses includes: The target flexible tube is scanned at each of the static limit positions and the corresponding static limit postures to obtain the first pose data.

6. The method according to claim 2, wherein, The multiple key nodes include at least two of the following: the extreme endpoints of the trajectory, the points of sudden velocity change, and the inflection points of the trajectory; The second pose data collected for multiple key points corresponding to each trajectory includes: The target flexible tube is sequentially adjusted to each of the key nodes and kept stationary; the three-dimensional data of each key node is obtained by scanning. The three-dimensional data of each key node are stitched together to obtain the second pose data.

7. The method according to claim 1, wherein, The step of adjusting the initial parameters based on the plurality of first pose data and the plurality of second pose data to obtain the target parameters of the train flexible tube simulation model includes: The adjustment operation of adjusting the initial parameters based on the plurality of first pose data and the plurality of second pose data is performed iteratively until the preset iteration condition is reached, and the target parameters are output.

8. The method according to claim 7, wherein, The adjustment operation at the (K+1)th time includes: The initial simulation model is trained based on the Kth set of model parameters obtained from the Kth adjustment operation, and the initial simulation model after the Kth training is completed is obtained. Obtain the Kth set of simulation data for the target flexible tube output by the initial simulation model after the Kth training; The static simulation data in the Kth group of simulation data is compared with the plurality of first pose data to obtain the first deviation value of the static simulation data compared with the plurality of first pose data; The dynamic simulation data in the Kth group of simulation data is compared with the plurality of second pose data to obtain a second deviation value of the dynamic simulation data compared with the plurality of second pose data; If the first deviation value and the second deviation value do not meet the preset data conditions, the initial parameters are adjusted for the (K+1)th time to obtain the (K+1)th set of model parameters.

9. The method according to claim 7, wherein, The preset iteration conditions include: the first deviation value and the second deviation value satisfy preset data conditions, and / or reach a preset number of iterations.

10. The method according to claim 1, wherein, The preset installation constraints include at least one of the following: the installation location, installation method, installation boundary restrictions, and train structure restrictions of the target flexible tube on the train.

11. A device for determining the installation information of a train flexible tube, comprising: The output module includes a train flexible tube simulation model that outputs target simulation data corresponding to the target flexible tube. The determination module includes determining the installation information of the target flexible tube on the train based on the target simulation data, wherein the train flexible tube simulation model is determined by target parameters; A fixing module is used to fix the target flexible tube to the posture testing equipment according to preset installation constraints. The first acquisition module is used to acquire multiple first pose data and multiple second pose data of the target flexible tube collected by the pose test equipment. The multiple first pose data are used to simulate the static limit position and static limit attitude of the target flexible tube when the train is stationary, and the multiple second pose data are used to simulate the maximum range of motion of the target flexible tube when the train is running. The second acquisition module is used to acquire the initial parameters of the train flexible tube simulation model for the target flexible tube; An adjustment module is used to adjust the initial parameters based on the plurality of first pose data and the plurality of second pose data to obtain the target parameters of the train flexible tube simulation model.

12. An electronic device, comprising: One or more processors; Memory, used to store one or more programs. Wherein, when the one or more programs are executed by the one or more processors, the one or more processors implement the method of any one of claims 10.

13. A train, comprising: The electronic device according to claim 12.

14. A computer-readable storage medium having stored thereon executable instructions that, when executed by a processor, cause the processor to perform the method of any one of claims 1 to 10.

15. A computer program product comprising a computer program that, when executed by a processor, implements the method according to any one of claims 1 to 10.

Images