Working machine rollover prediction method and device, working machine and readable storage medium

Abstract

The invention discloses an operation machine rollover prediction method and device, an operation machine and a readable storage medium, and relates to the technical field of operation machines. The method comprises the following steps: acquiring a three-dimensional model and mechanical quality parameters of an operation machine; determining sub-component node information of each sub-component of the operation machine based on the mechanical quality parameters and a preset total node number; determining sub-component gravity center information of each sub-component of the operation machine based on the three-dimensional model, the mechanical quality parameters and a preset total node number; constructing a finite element model based on preset tipping mark information, the sub-component node information and the sub-component gravity center information; determining a target gravity center and a stability coefficient of the operation machine based on the current state information of the operation machine and the finite element model; and determining the tipping risk of the working machine based on the target center of gravity and / or the stability factor. Three-dimensional modeling, finite element analysis and mechanics principles are combined, the rollover risk of the operation machine is predicted more accurately, and the safety and reliability of the operation machine are improved.

Description

Technical Field

[0001] The present application relates to the technical field of working machinery, and specifically to a method and device for predicting rollover of a working machinery, a working machinery, and a readable storage medium. Background Art

[0002] In the field of operating machinery, ensuring the safety of operating machinery is of vital importance, especially preventing the machinery from tipping over during operation. Such as excavators, loaders, cranes, rollers and other types of operating machinery. Such machinery may face the risk of tipping over in complex and changeable operating environments due to factors such as load changes, terrain undulations, and improper operation. Traditionally, the anti-tipping calculation of operating machinery such as excavators mainly relies on the center of gravity modeling of each component and the estimation of the overall center of gravity position combined with the joint angle data. Although this method can barely estimate the center of gravity state of the operating machinery on flat ground and without rotation, it has obvious limitations. Especially in the case of deflection, since the weight distribution of the operating machinery is often uneven, the torque situation of each component across the overall tipping line becomes extremely complicated, and it is difficult to accurately evaluate through simple split calculations. Summary of the invention

[0003] In view of the above-mentioned deficiencies in the prior art, the purpose of the embodiments of the present application is to provide a method and device for predicting rollover of a working machine, a working machine and a readable storage medium.

[0004] In order to achieve the above-mentioned object, the first aspect of the present application provides a method for predicting rollover of a working machine, comprising:

[0005] Obtain the three-dimensional model and mechanical quality parameters of the operating machinery;

[0006] Determine subcomponent node information of each subcomponent of the operating machine based on the machine mass parameter and the preset total node quantity;

[0007] Determine subcomponent gravity center information of each subcomponent of the operating machine based on the three-dimensional model, the machine mass parameters, and the preset total number of nodes;

[0008] Constructing a finite element model based on preset tipping mark information, subcomponent node information, and subcomponent center of gravity information;

[0009] Determine the target center of gravity and stability coefficient of the operating machine based on the current state information of the operating machine and the finite element model;

[0010] The tipping risk of the work machine is determined based on a target center of gravity and / or a stability factor.

[0011] In the embodiments of the present application, the mechanical mass parameters include the total mass of the working machine and the sub-component masses of each sub-component. Based on the mechanical mass parameters and the preset total number of nodes, the sub-component node information of each sub-component of the working machine is determined, including:

[0012] Based on the total mass and the preset total number of nodes, determine the node masses of all nodes corresponding to the working machine;

[0013] For each sub-component, based on the preset total number of nodes and the first ratio, determine the number of sub-component nodes, and use the node mass and the number of sub-component nodes as the sub-component node information, where the first ratio is the ratio of the sub-component mass to the total mass.

[0014] In the embodiments of the present application, the mechanical mass parameters include the total mass of the working machine and the sub-component masses of each sub-component. Based on the three-dimensional model, the mechanical mass parameters, and the preset total number of nodes, the sub-component centroid information of each sub-component of the working machine is determined, including:

[0015] For each sub-component, based on the three-dimensional model, determine the three-dimensional coordinates of each first node corresponding to the sub-component;

[0016] Based on all the three-dimensional coordinates, determine the extreme value range of the sub-component in the three-dimensional model;

[0017] Based on the three-dimensional model, determine the component structure range within the extreme value range;

[0018] Based on the preset total number of nodes and the first ratio, determine the number of sub-component nodes, where the first ratio is the ratio of the sub-component mass to the total mass;

[0019] Based on the number of sub-component nodes, determine the target first nodes within the component structure range;

[0020] Based on the three-dimensional coordinates of all the target first nodes, determine the sub-component centroid information of the sub-component.

[0021] In the embodiments of the present application, the preset tipping mark information includes connection node information, load-bearing node information, and tipping line node information. Based on the preset tipping mark information, the sub-component node information, and the sub-component centroid information, a finite element model is constructed, including:

[0022] In the preset initial finite element model, store each sub-component information in a partitioned manner based on the sub-component division information. The sub-component information includes the sub-component node information and the sub-component centroid information;

[0023] Based on the connection node information, the load-bearing node information, and the tipping line node information, construct the corresponding follower point information respectively to generate a finite element model.

[0024] In the embodiments of the present application, determining the target center of gravity and the stability coefficient of a working machine based on the current state information of the working machine and a finite element model includes:

[0025] Updating the parameter information in the finite element model based on the current state information of the working machine to obtain updated parameter information, where the parameter information includes sub-component information and follower point information;

[0026] Determining the target center of gravity of the working machine based on the updated parameter information;

[0027] Determining the target tipping line based on the tipping line node information in the finite element model;

[0028] For each target tipping line, determining stable nodes and tipping nodes based on the target tipping line and the updated parameter information to obtain a plurality of stable nodes and a plurality of tipping nodes;

[0029] Determining the stability coefficient based on the plurality of stable nodes, the plurality of tipping nodes, and the target tipping line.

[0030] In the embodiments of the present application, determining the stability coefficient based on the plurality of stable nodes, the plurality of tipping nodes, and the target tipping line includes:

[0031] Determining a first distance based on the relative position of the stable node and the target tipping line;

[0032] Determining the sum of the first moments of all stable nodes as the first stability moment, where the first moment is equal to the product of the first distance and the gravity of the stable node;

[0033] Determining a second distance based on the relative position of the tipping node and the target tipping line;

[0034] Determining the sum of the second moments of all tipping nodes as the first tipping moment, where the second moment is equal to the product of the second distance and the gravity of the tipping node;

[0035] Determining the ratio of the first stability moment to the first tipping moment as the stability coefficient.

[0036] In the embodiments of the present application, determining the stability coefficient based on all stable nodes, all tipping nodes, and the target tipping line includes:

[0037] When the moving speed of the working device of the working machine is greater than a preset speed threshold, determining the first current position information and the first historical position information of the stable node based on a preset time interval, and determining the second current position information and the second historical position information of the tipping node;

[0038] Determining the first acceleration of the stable node in the gravity direction based on the first current position information, the first historical position information, and the preset time interval;

[0039] Determine a third distance based on the relative positions of the stable nodes and the target tipping line;

[0040] Determine the sum of the third moments of all the stable nodes as the second stability moment, where the third moment is equal to the product of the third distance and a first value, and the first value is the sum of the gravity of the stable node and a first acceleration;

[0041] Determine a second acceleration of the tipping node in the direction of gravity based on the second current position information, the second historical position information, and a preset time interval;

[0042] Determine a fourth distance based on the relative position of the tipping node and the target tipping line;

[0043] Determine the sum of the fourth moments of all the tipping nodes as the second tipping moment, where the fourth moment is equal to the product of the fourth distance and a second value, and the second value is the sum of the gravity of the tipping node and the second acceleration;

[0044] Determine the ratio of the second stability moment to the second tipping moment as the stability coefficient.

[0045] In the embodiments of the present application, determining the tipping risk of the working machine based on the target center of gravity and / or the stability coefficient includes:

[0046] Determine the tipping risk based on the relative position of the target center of gravity and the target tipping line, where the target tipping line is determined based on the tipping line node information in the preset tipping mark information, and / or;

[0047] Determine the tipping risk based on the stability coefficient and a preset level threshold.

[0048] In the embodiments of the present application, determining the tipping risk based on the relative position of the target center of gravity and the target tipping line includes:

[0049] When the distance between the target center of gravity and the target tipping line is less than a preset distance value, or when the target center of gravity is on the risk side of the target tipping line, determine that the working machine has a tipping risk;

[0050] When the distance between the target center of gravity and the target tipping line is greater than the preset distance value and the target center of gravity is on the safe side of the target tipping line, determine that the working machine has no tipping risk;

[0051] Determining the tipping risk based on the stability coefficient and a preset level threshold includes:

[0052] Determine the risk level according to the stability coefficient and the preset level threshold;

[0053] When the risk level is greater than or equal to the preset level, determine that the working machine has a tipping risk;

[0054] When the risk level is less than the preset level, it is determined that the working machine has no tipping risk.

[0055] The second aspect of the present application provides a tipping prediction device for a working machine, including:

[0056] A memory configured to store instructions;

[0057] A processor configured to call instructions from the memory and, when executing the instructions, be able to implement the tipping prediction method for the working machine as described in the above embodiments.

[0058] The third aspect of the present application provides a working machine, including:

[0059] The tipping prediction device for the working machine as described in the above embodiments.

[0060] The fourth aspect of the present application provides a machine-readable storage medium, on which instructions are stored, and the instructions are used to cause a machine to execute the tipping prediction method for the working machine as described in the above embodiments.

[0061] Through the above technical solutions, a three-dimensional model and mechanical mass parameters of the working machine are obtained; the sub-component node information of each sub-component of the working machine is determined based on the mechanical mass parameters and the preset total number of nodes; the sub-component center-of-gravity information of each sub-component of the working machine is determined based on the three-dimensional model, the mechanical mass parameters, and the preset total number of nodes; a finite element model is constructed based on the preset tipping mark information, the sub-component node information, and the sub-component center-of-gravity information; the target center of gravity and the stability coefficient of the working machine are determined based on the current state information of the working machine and the finite element model; the tipping risk of the working machine is determined based on the target center of gravity and / or the stability coefficient. Combining three-dimensional modeling, finite element analysis, and mechanical principles can more accurately predict the tipping risk of the working machine, providing strong support for the design, use, and maintenance of the working machine. At the same time, it also improves the safety and reliability of the working machine and reduces the losses caused by tipping accidents.

[0062] Other features and advantages of the embodiments of the present application will be described in detail in the subsequent specific implementation part. BRIEF DESCRIPTION OF THE DRAWINGS

[0063] The drawings are used to provide a further understanding of the embodiments of the present application and constitute a part of the specification, and are used together with the following specific implementation to explain the embodiments of the present application, but do not constitute a limitation to the embodiments of the present application. In the drawings:

[0064] Figure 1 Schematically shows a flowchart of a tipping prediction method for a working machine according to an embodiment of the present application;

[0065] Figure 2Schematically shows a schematic diagram of node division according to an embodiment of the present application;

[0066] Figure 3 Schematically shows a schematic diagram of information storage of a finite element model according to an embodiment of the present application;

[0067] Figure 4 Schematically shows a schematic diagram of a tipping risk area according to an embodiment of the present application;

[0068] Figure 5 Schematically shows a structural block diagram of a tipping prediction device for a work machine according to an embodiment of the present application. Detailed implementation manners

[0069] To make the objectives, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present application. It should be understood that the specific implementation manners described herein are only for explaining and illustrating the embodiments of the present application, and are not used to limit the embodiments of the present application. All other embodiments obtained by those of ordinary skill in the art based on the embodiments in the present application without creative efforts belong to the scope protected by the present application.

[0070] It should be noted that the acquisition, transmission, storage, use, processing, etc. of data in the technical solutions of the present application all comply with the relevant provisions of national laws and regulations. In the embodiments of the present application, some industry-existing solutions such as certain software, components, models, etc. may be mentioned, and they should be regarded as exemplary. The purpose is only to illustrate the feasibility in the implementation of the technical solutions of the present application, but it does not mean that the applicant has already or necessarily used this solution.

[0071] It should be noted that if there are directional indications (such as up, down, left, right, front, back...) involved in the embodiments of the present application, the directional indications are only used to explain the relative positional relationship and movement conditions between components in a certain specific posture (as shown in the drawings). If this specific posture changes, the directional indications will also change accordingly.

[0072] In addition, if there are descriptions involving "first", "second", etc. in the embodiments of the present application, the descriptions of "first", "second", etc. are only for descriptive purposes and cannot be understood as indicating or implying their relative importance or implicitly indicating the quantity of the indicated technical features. Thus, the features defined with "first" and "second" may explicitly or implicitly include at least one of such features. In addition, the technical solutions between various embodiments can be combined with each other, but it must be based on the ability of those of ordinary skill in the art to implement. When the combination of technical solutions results in contradictions or cannot be implemented, it should be considered that such a combination of technical solutions does not exist and is not within the scope of protection required by the present application.

[0073] Figure 1 Schematically shows a flowchart of a tipping prediction method for a construction machine according to an embodiment of the present application. As Figure 1 shown, an embodiment of the present application provides a tipping prediction method for a construction machine, and the method may include the following steps:

[0074] Step 100, obtain the three-dimensional model and mechanical mass parameters of the construction machine;

[0075] In this embodiment, it should be noted that the three-dimensional model refers to an accurate three-dimensional representation of the construction machine obtained through CAD (Computer Aided Design) or other three-dimensional modeling software; the mechanical mass parameters may include the total mass of the construction machine, the mass distribution of each component, etc. The sub-component division information is used to divide the construction machine into multiple sub-components to more carefully analyze the impact of each component on the overall stability.

[0076] Step 200, determine the sub-component node information of each sub-component of the construction machine based on the mechanical mass parameters and the preset total number of nodes;

[0077] Step 300, determine the sub-component centroid information of each sub-component of the construction machine based on the three-dimensional model, the mechanical mass parameters, and the preset total number of nodes.

[0078] It should be noted that the sub-component node information is that in the three-dimensional model, each sub-component is composed of a series of nodes, and the positions and connection relationships of these nodes determine the shape and structure of the sub-component. The sub-component centroid information refers to the centroid position calculated based on the mass and shape of the sub-component. The centroid is the point of action of the resultant force of the gravity acting on the object and has an important impact on the stability and tipping risk of the object.

[0079] Step 400, construct a finite element model based on the preset tipping marking information, the sub-component node information, and the sub-component centroid information;

[0080] It should be noted that the preset tipping marking information includes presetting some key points or conditions that may cause tipping according to the design and use experience of the construction machine. Combining the sub-component node information, the sub-component centroid information, and the preset tipping marking information, a finite element model is constructed. The finite element model is a mathematical model that discretizes a continuum into a finite number of interconnected unit bodies and is used to simulate and analyze the mechanical behavior of complex structures.

[0081] Step 500, determine the target centroid and stability coefficient of the construction machine based on the current state information of the construction machine and the finite element model;

[0082] It should be noted that the target center of gravity refers to the overall center of gravity position of the working machine calculated in the finite element model based on the current state information, such as the working posture, load condition, etc. The stability coefficient is used to evaluate the stability of the working machine in the current state. The stability coefficient is usually related to factors such as the center of gravity height and the support area of the working machine.

[0083] Step 600, determine the tipping risk of the working machine based on the target center of gravity and / or the stability coefficient.

[0084] It should be noted that based on the target center of gravity and / or the stability coefficient, combined with the design parameters and usage experience of the working machine, its tipping risk is evaluated. Specifically, if the target center of gravity is too high or the stability coefficient is too low, the working machine may face a relatively high tipping risk.

[0085] In this embodiment, a three-dimensional model and mechanical mass parameters of the working machine are obtained; sub-component node information of each sub-component of the working machine is determined based on the mechanical mass parameters and the preset total number of nodes; sub-component center of gravity information of each sub-component of the working machine is determined based on the three-dimensional model, mechanical mass parameters, and the preset total number of nodes; a finite element model is constructed based on the preset tipping mark information, sub-component node information, and sub-component center of gravity information; the target center of gravity and the stability coefficient of the working machine are determined based on the current state information of the working machine and the finite element model; the tipping risk of the working machine is determined based on the target center of gravity and / or the stability coefficient. Combining three-dimensional modeling, finite element analysis, and mechanical principles can more accurately predict the tipping risk of the working machine, providing strong support for the design, use, and maintenance of the working machine. At the same time, it also improves the safety and reliability of the working machine and reduces the losses caused by tipping accidents. In addition, in this embodiment, the inseparable center of gravity model of the working machine is converted into a separable finite element mass model, and a single component can simultaneously affect the stabilizing moment and the tipping moment, making the stability calculation accuracy of the excavator higher, and working conditions such as slopes, semi-rotation, and dynamics can be accurately calculated.

[0086] In one embodiment, the mechanical mass parameters include the total mass of the working machine and the sub-component masses of each sub-component. Determining the sub-component node information of each sub-component of the working machine based on the mechanical mass parameters and the preset total number of nodes includes:

[0087] Determine the node mass of all nodes corresponding to the working machine based on the total mass and the preset total number of nodes;

[0088] For each sub-component, determine the number of sub-component nodes based on the preset total number of nodes and the first ratio, and use the node mass and the number of sub-component nodes as the sub-component node information, where the first ratio is the ratio of the sub-component mass to the total mass.

[0089] In this embodiment, it should be noted that the preset total number of nodes is preset according to the refinement degree of the model. Obtain the total mass of the working machine, and evenly distribute the total mass to these nodes according to the preset total number of nodes, so as to obtain the node mass of each node. For each sub-component, obtain its mass. Calculate the ratio of the sub-component mass to the total mass, and this ratio can reflect the importance of the sub-component in the overall structure. Multiply this ratio by the preset total number of nodes to obtain the number of nodes of each sub-component. For each sub-component, determine the three-dimensional coordinates of all the first nodes based on its three-dimensional model, and use the node mass of the node and the number of nodes corresponding to the sub-component as the node information of the sub-component.

[0090] In one embodiment, the mechanical mass parameters include the total mass of the working machine and the sub-component masses of each sub-component. Based on the three-dimensional model, the mechanical mass parameters, and the preset total number of nodes, determine the sub-component centroid information of each sub-component of the working machine, including:

[0091] For each sub-component, determine the three-dimensional coordinates of the corresponding first nodes of the sub-component based on the three-dimensional model;

[0092] Based on all the three-dimensional coordinates, determine the extreme value range of the sub-component in the three-dimensional model;

[0093] Based on the three-dimensional model, determine the component structure range within the extreme value range;

[0094] Based on the preset total number of nodes and the first ratio, determine the number of sub-component nodes, where the first ratio is the ratio of the sub-component mass to the total mass;

[0095] Based on the number of sub-component nodes, determine the target first nodes within the component structure range;

[0096] Based on the three-dimensional coordinates of all the target first nodes, determine the sub-component centroid information of the sub-component.

[0097] Reference Figure 2 , in this embodiment, it should be noted that the first nodes are all the nodes included in the sub-component. Based on the three-dimensional coordinates of all the first nodes, determine the maximum and minimum coordinate values corresponding to the three coordinate axes of the sub-component in the three-dimensional model, so as to obtain the extreme value range of the sub-component. The node range of each node (x i , y i , z i ) of the sub-component corresponds to: x min ≤x i ≤x max , y min ≤y i ≤y max , z min ≤z i ≤z maxBased on a preset scale s, which is a very small value, divide the extreme value range. The number of divided nodes N can be calculated by the following formula:

[0098]

[0099] In a three-dimensional model, determine a range that includes the entity structure of the sub-component according to the geometric shape and structural characteristics of the sub-component. In one embodiment, the component structure range can be slightly larger than the actual structure range of the sub-component to ensure that all important structural characteristics are included.

[0100] Within the component structure range, randomly sample according to the number of sub-component nodes. The number of sampled nodes is equal to the number of sub-component nodes of the sub-component to obtain a set of nodes representing the sub-component, that is, the target first nodes. Based on the three-dimensional coordinates of all target first nodes and their respective node masses, use the weighted average method or the average method to calculate the centroid position of the sub-component. This centroid position is the sub-component centroid information of the sub-component.

[0101] In this embodiment, detailed node information and centroid information are generated for each sub-component, providing an effective data basis for subsequent finite element model construction, stability analysis, and tipping risk prediction.

[0102] In one embodiment, the preset tipping marker information includes connection node information, load-bearing node information, and tipping line node information. Construct a finite element model based on the preset tipping marker information, sub-component node information, and sub-component centroid information, including:

[0103] Refer to Figure 3 , and store each sub-component information in partition based on the sub-component division information in the preset initial finite element model. The sub-component information includes sub-component node information and sub-component centroid information;

[0104] Construct corresponding follower point information based on the connection node information, load-bearing node information, and tipping line node information to generate a finite element model.

[0105] In this embodiment, it should be noted that the preset tipping marker information includes connection node information, load-bearing node information, and tipping line node information. The connection node information is the key point of connection between each sub-component or component in the model, which is crucial for ensuring the integrity and stability of the entire structure. The load-bearing node information is the point that bears the main load in the model, and their positions and characteristics are crucial for evaluating the load-bearing capacity and safety of the structure. The tipping line node information defines the potential lines or surfaces that may cause the structure to tip. By identifying the tipping line nodes, a more in-depth assessment of the structure's stability can be carried out.

[0106] It should be noted that in the preset initial finite element model, the information of each sub-component is stored in partitions according to the sub-component division information. The sub-component information includes sub-component node information and sub-component centroid information. The node information may include the three-dimensional coordinates of the nodes, the node mass, etc.; the centroid information provides the central position of the mass distribution of the sub-component.

[0107] In this embodiment, based on the connection node information, load-bearing node information, and tipping line node information, the corresponding follower point information is constructed respectively. The follower point information refers to the points associated with these key nodes in the finite element model, which will move as the model deforms, thus providing important information about the structural behavior. For connection nodes, follower points may be used to simulate the deformation and stress distribution at the connection; for load-bearing nodes, follower points may be used to monitor load transfer and stress concentration; for tipping line nodes, follower points may be used to evaluate the tipping risk and stability of the structure. For unfixed mass nodes, such as the moving oil circuit in the hydraulic system, the driver, and the amount of oil in the fuel tank, since it is not convenient to obtain real-time values, estimated values are taken. For example, the driver's weight is taken as 70 kg, and other dynamic data are updated by reading the sensor data in real time. By pre-specifying the connection node information, load-bearing node information, tipping line node information, etc. corresponding to the construction machinery in the finite element model, in practical applications, there is no need to perform analysis and calculations for connection nodes, load-bearing nodes, tipping lines, sub-component centroids, etc. These nodes can be directly accessed through the access sequence numbers of the finite element model, saving computing resources and improving the efficiency of judging the tipping risk of the construction machinery.

[0108] After constructing all the necessary follower point information, this information is integrated into the initial finite element model to generate the final finite element model. This model will include the information of all sub-components, node connections, material properties, boundary conditions, etc., and is ready for further finite element analysis.

[0109] Reference Figure 3 , in the finite element model, the construction machinery may include sub-components such as a chassis unit, a boom unit, an arm unit, a bucket unit, and a dynamic unit. The sub-components may include the centroid node information and follower point information of different attached components. For example, the boom unit includes centroid node information: boom centroid node; and follower point information: boom joint node.

[0110] In this embodiment, the constructed finite element model can fully consider the complexity of the structure, the load-bearing capacity, and the stability requirements. This is crucial for evaluating the performance of the construction machinery, optimizing the design, and ensuring safety.

[0111] In one embodiment, determining the target centroid and stability coefficient of the construction machinery based on the current state information of the construction machinery and the finite element model includes:

[0112] Update the parameter information in the finite element model based on the current state information of the work machine, where the parameter information includes sub-component information and follower point information;

[0113] Determine the target center of gravity of the work machine based on the updated parameter information;

[0114] Determine the target tipping line based on the tipping line node information in the finite element model;

[0115] For each target tipping line, determine the stable nodes and tipping nodes based on the target tipping line and the updated parameter information;

[0116] Determine the stability coefficient based on the stable nodes, tipping nodes, and the target tipping line.

[0117] In this embodiment, it should be noted that the current state information may include factors that may affect its performance, such as the current working conditions, load conditions, component wear degree, environmental temperature, etc. of the work machine. The current state information may also include the chassis tilt angle, upper body slewing angle, boom angle, stick angle, bucket angle, bucket capacity weight, etc.

[0118] According to the current state information, adjust the information of each sub-component in the finite element model, such as position, size, center of gravity, etc. A follower point is a point associated with a key node, used to monitor the deformation and stress state of the structure. According to the current state information, adjust the position or number of follower points to more accurately reflect the actual behavior of the structure. Using the updated sub-component information and follower point information, calculate the overall mass distribution of the work machine. Determine the target center of gravity position according to the mass distribution. For example, the target center of gravity is expressed as where, where, n represents the number of nodes of the work machine; x i represents the horizontal axis coordinate of the i-th node; y i represents the vertical axis coordinate of the i-th node; z i represents the vertical axis coordinate of the i-th node.

[0119] In the finite element model, the tipping line nodes define the potential lines or surfaces that may cause the structure to tip over. According to the current state information and the updated parameter information, re-evaluate the position and characteristics of the tipping line nodes. Determine the target tipping line, that is, the boundary line that may cause the work machine to tip over.

[0120] For each target tipping line, analyze its relationship with the updated parameter information, especially the sub-component information and the following point information. Determine the stable nodes and the tipping nodes. The stable nodes provide the moment to resist tipping during the tipping process. The tipping nodes are the key points that may cause structural instability during the tipping process. The stability coefficient is a quantitative index to measure the stability of the working machine. Calculate the stability coefficient according to the balance relationship between the moment to resist tipping provided by the stable nodes and the tipping moment caused by the tipping nodes. Consider the influence of the geometric characteristics of the target tipping line and the overall mass distribution of the working machine on the stability coefficient. The stability state of the working machine can be evaluated by comparing the stability coefficient with a predetermined safety threshold.

[0121] In this embodiment, adjust the parameter information in the finite element model according to the actual situation to ensure that the working machine can maintain sufficient stability under actual working conditions.

[0122] In one embodiment, determining the stability coefficient based on the stable nodes, the tipping nodes, and the target tipping line includes:

[0123] Determine a first distance based on the relative position of the stable node and the target tipping line;

[0124] Determine the sum of the first moments of the stable nodes as the first stable moment, where the first moment is equal to the product of the first distance and the gravity of the stable node;

[0125] Determine a second distance based on the relative position of the tipping node and the target tipping line;

[0126] Determine the sum of the second moments of the tipping nodes as the first tipping moment, where the second moment is equal to the product of the second distance and the gravity of the tipping node;

[0127] Determine the ratio of the first stable moment to the first tipping moment as the stability coefficient.

[0128] In this embodiment, it should be noted that the first distance refers to the vertical distance between the stable node and the reference plane, and the reference plane is the plane determined by the target tipping line and the vertical direction of gravity. For each stable node, calculate the moment generated by its gravity, that is, the first moment. The first moment is equal to the product of the first distance and the gravity of the stable node. If there are multiple stable nodes, then accumulate the first moments of all stable nodes to obtain the first stable moment.

[0129] Similarly, the second distance refers to the vertical distance between the tipping node and the reference plane, where the reference plane is the plane determined by the target tipping line and the vertical direction of gravity. For each tipping node, calculate the moment generated by its gravity, i.e., the second moment. The second moment is equal to the product of the second distance and the gravity of the tipping node. If there are multiple tipping nodes, accumulate the second moments of all tipping nodes to obtain the first tipping moment. Determine the ratio of the first stability moment to the first tipping moment as the stability coefficient.

[0130] Further, in one embodiment, determining the stability coefficient based on the stable node, the tipping node, and the target tipping line includes:

[0131] When the moving speed of the working device of the working machine is greater than the preset speed threshold, determine the first current position information and the first historical position information of the stable node based on a preset time interval, and determine the second current position information and the second historical position information of the tipping node;

[0132] Determine the first acceleration of the stable node in the direction of gravity based on the first current position information and the first historical position information;

[0133] Determine the third distance based on the relative position of the stable node and the target tipping line;

[0134] Determine the sum of the third moments of the stable nodes as the second stability moment, where the third moment is equal to the product of the third distance and the first value, and the first value is the sum of the gravity of the stable node and the first acceleration;

[0135] Determine the second acceleration of the tipping node in the direction of gravity based on the second current position information and the second historical position information;

[0136] Determine the fourth distance based on the relative position of the tipping node and the target tipping line;

[0137] Determine the sum of the fourth moments of the tipping nodes as the second tipping moment, where the fourth moment is equal to the product of the fourth distance and the second value, and the second value is the sum of the gravity of the tipping node and the second acceleration;

[0138] Determine the ratio of the second stability moment to the second tipping moment as the stability coefficient.

[0139] In this embodiment, it should be noted that the working device of the working machine refers to the key component for the working machine to perform specific working tasks. For example, the working device of an excavator includes a bucket; the working device of a loader includes a bucket; the working device of a crane includes a hoisting mechanism, a traveling mechanism, a luffing mechanism, a slewing mechanism, etc.; the working device of a roller includes a road roller. In one embodiment, if it is difficult to calculate the moving speed of the working device, the traveling speed of the working machine can also be considered. Compare the traveling speed of the working machine with a preset speed threshold.

[0140] It should be noted that when the moving speed of the working device of the working machine is greater than the preset speed threshold, start recording the position information of the stable node and the tipping node based on a preset time interval. For the stable node, record its first current position information and first historical position information. The first current position information is the position of the stable node at the current time point, and the first historical position information includes the position of the stable node at the previous time point. The first historical position information can also include the position of the stable node at an even more previous time point compared to the previous time point, and so on, and can include the positions of the stable node at multiple previous time points. For the tipping node, similarly record its second current position information and second historical position information. Among them, the second current position information is the position of the tipping node at the current time point, and the second historical position information includes the position of the tipping node at the previous time point. The second historical position information can also include the position of the tipping node at an even more previous time point compared to the previous time point, and so on, and can include the positions of the tipping node at multiple previous time points.

[0141] Specifically, obtain the first current vertical axis direction position in the first current position information of the stable node; and obtain the first historical vertical axis direction position in the first historical position information. According to the position difference between the first current vertical axis direction position and the first historical vertical axis direction position, the position change of the stable node in the gravity direction can be determined. According to the ratio of this position difference to the preset time interval, the speed at the current time point can be calculated as the current speed. The following formula can be referred to:

[0142]

[0143] Among them, V zt represents the current speed; Z t represents the first current vertical axis direction position; Z t-s represents the first historical vertical axis direction position; s represents the preset time interval.

[0144] Similarly, the speed at the previous time point can be calculated as the historical speed; subtract the historical speed from the current speed to obtain the speed difference; according to the ratio of this speed difference to the preset time interval, the first acceleration of the stable node in the gravity direction can be obtained.

[0145] The following formula can be referred to:

[0146]

[0147] Wherein, a z represents the first acceleration; V zt represents the current speed; V z(t-s) represents the historical speed; s represents the preset time interval.

[0148] Similarly, based on the second current position information and the second historical position information of the tipping node, the kinematic formula can also be used to calculate the second acceleration of the tipping node in the direction of gravity.

[0149] It should be noted that the third distance refers to the vertical distance between the stable node and the reference plane, and the reference plane is the plane determined by the target tipping line and the vertical direction of gravity. For each stable node, the third moment is calculated. The third moment is equal to the product of the third distance and the first value, and the first value is the sum of the gravity of the stable node and the first acceleration. If there are multiple stable nodes, the third moments of all stable nodes are accumulated to obtain the second stable moment. Similarly, based on the relative position of the tipping node and the target tipping line, the fourth distance is determined, and the sum of the fourth moments of the tipping node is calculated as the second tipping moment. The ratio of the second stable moment to the second tipping moment is determined as the stability coefficient.

[0150] In this embodiment, considering the traveling speed of the working machine makes the tipping analysis closer to the actual application scenario and improves the effectiveness and real-time performance of the tipping risk prediction.

[0151] In one embodiment, determining the tipping risk of the working machine based on the target center of gravity and / or the stability coefficient includes:

[0152] Determining the tipping risk based on the relative position of the target center of gravity and the target tipping line, wherein the target tipping line is determined based on the tipping line node information in the preset tipping mark information, and / or;

[0153] Determining the tipping risk based on the stability coefficient and the preset level threshold.

[0154] In this embodiment, it should be noted that the preset tipping mark information includes tipping line node information, and the boundary line most likely to cause the tipping of the working machine under specific working conditions can be determined, that is, the target tipping line. The tipping line node information in the finite element model can be used to determine the boundary line most likely to cause the tipping of the working machine under specific working conditions, that is, the target tipping line. When performing calculation and analysis using the finite element model, the tipping line node information can be stored in the finite element model in advance based on the preset tipping mark information, and the target tipping line can be directly determined based on the tipping node information without real-time analysis and calculation, improving the efficiency of tipping judgment.

[0155] It should be noted that according to the current state information of the working machine, the target center of gravity position of the working machine can be calculated. The target tipping line refers to the boundary line most likely to cause the tipping of the working machine under specific working conditions. Whether the working machine has a tipping risk can be determined based on the relative position between the target center of gravity and the target tipping line, that is, the closer the target center of gravity of the working machine is to the target tipping line, the greater the tipping risk. In one embodiment, multiple distance thresholds can also be set for the distance between the target center of gravity and the target tipping line, corresponding to multiple different risk levels; the smaller the distance, the higher the risk level; when the preset risk level is reached, it is determined that there is a tipping risk. Different risk degrees can also be determined based on different risk levels, for example, more or fewer level divisions such as no risk, low risk, medium risk, and high risk.

[0156] It should be noted that a series of grade thresholds of the stability coefficient can be set according to the design requirements, safety standards, and actual working conditions of the working machine. The calculated stability coefficient is compared with the preset grade thresholds. Different preset grade thresholds can correspond to different risk levels of the working machine, for example, more or fewer levels such as no risk, low risk, medium risk, and high risk.

[0157] Specifically, in one embodiment, determining the tipping risk based on the relative position between the target center of gravity and the target tipping line includes:

[0158] When the distance between the target center of gravity and the target tipping line is less than the preset distance value, or when the target center of gravity is on the risk side of the target tipping line, it is determined that the working machine has a tipping risk;

[0159] When the distance between the target center of gravity and the target tipping line is greater than the preset distance value and the target center of gravity is on the safe side of the target tipping line, it is determined that the working machine does not have a tipping risk;

[0160] It should be noted that the target tipping line refers to the boundary line that is most likely to cause the tipping of a working machine under specific working conditions. If the target center of gravity approaches or exceeds the target tipping line, the tipping risk of the working machine is relatively high. The risk side of the target tipping line refers to the side that may cause the tipping of the working machine; the safe side of the target tipping line refers to the other side compared to the risk side, which will not cause the tipping of the working machine. By comparing the relative positions of the target center of gravity and the target tipping line, when the distance between the target center of gravity and the target tipping line is less than the preset distance value, or when the target center of gravity is on the risk side of the target tipping line, it is determined that the working machine has a tipping risk. When the distance between the target center of gravity and the target tipping line is greater than the preset distance value and the target center of gravity is on the safe side of the target tipping line, it is determined that the working machine has no tipping risk. The target tipping line can refer to Figure 4 the position of the red line shown in Figure 4 and the area where the target center of gravity is located and has a tipping risk can refer to Figure 4 the red area shown in. As

[0161] stated, for the position where the target center of gravity is located, the red area outside the red line indicates that the working machine has a direct tipping risk; the area between the red line and the green line indicates that the working machine has a tipping risk; and the area within the green line indicates that the working machine has no tipping risk.

[0162] Determining the tipping risk based on the stability coefficient and the preset grade threshold includes:

[0163] Determining the risk grade according to the stability coefficient and the preset grade threshold;

[0164] When the risk grade is greater than or equal to the preset grade, it is determined that the working machine has a tipping risk;

[0165] It should be noted that different preset level thresholds can correspond to different risk levels of the working machine. For example, there are no risks, low risks, medium risks, and high risks, etc. If the stability coefficient is higher than a certain preset level threshold, the tipping risk of the working machine is higher. Suppose the preset level thresholds include 1, 0.8, 0.6, 0.4, and 0.2, corresponding to the absolute tipping risk, high risk, medium risk, low risk, and no risk levels respectively. When the stability coefficient is greater than 1, it indicates that tipping will definitely occur, and it is at the absolute tipping risk level; when it is greater than 0.8, it indicates a relatively high tipping risk, and it is at the high risk level. When the stability coefficient is small, such as less than 0.2, it indicates that there is no tipping risk for the working machine. Risk prediction and tipping control can also be carried out according to the change trend of the stability coefficient. The preset risk level can be set based on the requirements for the tipping risk in actual application needs. For example, the preset level can be set to the low risk level, or it can be set to the medium risk level, etc. When the risk level is greater than or equal to the preset level, it is determined that the working machine has a tipping risk. When the risk level is less than the preset level, it is determined that the working machine has no tipping risk.

[0166] In one embodiment, the tipping risk can also be initially judged by comparing the relative positions of the target center of gravity and the target tipping line, and then the risk level can be further confirmed by calculating the stability coefficient and comparing it with the preset level threshold.

[0167] In this embodiment, through the effective prediction of the tipping risk, the working safety and stability of the working machine are improved.

[0168] Figure 5 Schematically shows a structural block diagram of a tipping prediction device for a working machine according to an embodiment of the present application. As Figure 5 shown, an embodiment of the present application provides a tipping prediction device for a working machine, which may include:

[0169] A memory X10, configured to store instructions;

[0170] A processor X20, configured to call instructions from the memory X10 and be able to implement the tipping prediction method for the working machine as described in the above embodiment when executing the instructions.

[0171] An embodiment of the present application further provides a working machine, including:

[0172] The tipping prediction device for the working machine as described in the above embodiment.

[0173] An embodiment of the present application further provides a machine-readable storage medium, on which instructions are stored, and these instructions are used to make a machine execute the tipping prediction method for the working machine as described in the above embodiment.

[0174] Those skilled in the art should understand that the embodiments of the present application can be provided as methods, systems, or computer program products. Therefore, the present application can take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present application can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0175] The present application is described with reference to the flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each flow and / or block in the flowchart and / or block diagram, as well as the combination of flows and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing devices to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing devices generate a device for realizing the functions specified in Figure 1 one or more of the processes or multiple processes and / or blocks Figure 1 one or more of the blocks or multiple blocks.

[0176] These computer program instructions can also be stored in a computer-readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer-readable memory generate a manufactured article including an instruction device, and the instruction device realizes the functions specified in Figure 1 one or more of the processes or multiple processes and / or blocks Figure 1 one or more of the blocks or multiple blocks.

[0177] These computer program instructions can also be loaded onto a computer or other programmable data processing device, so that a series of operation steps are executed on the computer or other programmable device to generate a computer-implemented process. Thus, the instructions executed on the computer or other programmable device provide steps for realizing the functions specified in Figure 1 one or more of the processes or multiple processes and / or blocks Figure 1 one or more of the blocks or multiple blocks.

[0178] In a typical configuration, a computing device includes one or more processors (CPUs), an input / output interface, a network interface, and memory.

[0179] The memory may include non-permanent memory in a computer-readable medium, in the form of random access memory (RAM) and / or non-volatile memory, such as read-only memory (ROM) or flash memory (flash RAM). The memory is an example of a computer-readable medium.

[0180] A computer-readable medium includes both permanent and non-permanent, removable and non-removable media and can implement information storage by any method or technology. The information can be computer-readable instructions, data structures, program modules, or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, compact disc read-only memory (CD-ROM), digital versatile disc (DVD) or other optical storage, magnetic cassette tapes, disk storage or other magnetic storage devices, or any other non-transitory medium that can be used to store information that can be accessed by a computing device. As defined herein, a computer-readable medium does not include transitory computer-readable media such as modulated data signals and carrier waves.

[0181] It should also be noted that the term "comprising," "including," or any other variant thereof is intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that includes a series of elements includes not only those elements but also other elements not expressly listed, or elements that are inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the statement "comprising one..." does not exclude the presence of additional identical elements in the process, method, article, or apparatus that includes the element.

[0182] The above are only embodiments of the present application and are not used to limit the present application. For those skilled in the art, various changes and modifications can be made to the present application. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application shall be included within the scope of the claims of the present application.

Claims

1. A tipping prediction method for a work machine, characterized in that, Including: Obtaining a three-dimensional model of the working machine and mechanical mass parameters; Determining sub-component node information of each sub-component of the working machine based on the mechanical mass parameters and a preset total number of nodes; Determining sub-component center-of-gravity information of each sub-component of the working machine based on the three-dimensional model, the mechanical mass parameters, and the preset total number of nodes; Constructing a finite element model based on preset tipping mark information, the sub-component node information, and the sub-component center-of-gravity information; Determining the target center of gravity and stability coefficient of the working machine based on the current state information of the working machine and the finite element model; Determining the tipping risk of the working machine based on the target center of gravity and / or the stability coefficient; 2. The tipping prediction method for a work machine according to claim 1, wherein The mechanical mass parameters include the total mass of the working machine and the sub-component masses of each sub-component. Determining the sub-component node information of each sub-component of the working machine based on the mechanical mass parameters and a preset total number of nodes includes: Determining the node masses of all nodes corresponding to the working machine based on the total mass and the preset total number of nodes; For each sub-component, determining the number of sub-component nodes based on the preset total number of nodes and a first ratio, and taking the node mass and the number of sub-component nodes as the sub-component node information, where the first ratio is the ratio of the sub-component mass to the total mass.

3. The tipping prediction method for a work machine according to claim 1, wherein, The mechanical mass parameters include the total mass of the working machine and the sub-component masses of each sub-component. Determining the sub-component center-of-gravity information of each sub-component of the working machine based on the three-dimensional model, the mechanical mass parameters, and the preset total number of nodes includes: For each sub-component, determining the three-dimensional coordinates of each first node corresponding to the sub-component based on the three-dimensional model; Determining the extreme value range of the sub-component in the three-dimensional model based on all the three-dimensional coordinates; Determining the component structure range within the extreme value range based on the three-dimensional model; Determining the number of sub-component nodes based on the preset total number of nodes and a first ratio, where the first ratio is the ratio of the sub-component mass to the total mass; Determining target first nodes within the component structure range based on the number of sub-component nodes; Determining the sub-component center-of-gravity information of the sub-component based on the three-dimensional coordinates of all the target first nodes.

4. The tipping prediction method for a work machine according to claim 1, wherein, The preset tipping mark information includes connection node information, load-bearing node information, and tipping line node information. Constructing a finite element model based on the preset tipping mark information, the sub-component node information, and the sub-component center-of-gravity information includes: Storing information of each sub-component in a partitioned manner in a preset initial finite element model, where the sub-component information includes sub-component node information and sub-component center-of-gravity information; Constructing corresponding follower point information respectively based on the connection node information, the load-bearing node information, and the tipping line node information to generate a finite element model.

5. The tipping prediction method for a work machine according to claim 1, characterized in that, Determining the target center of gravity and stability coefficient of the working machine based on the current state information of the working machine and the finite element model includes: Update the parameter information in the finite element model based on the current state information of the construction machine to obtain the updated parameter information, where the parameter information includes sub-component information and follower point information; Determine the target center of gravity of the construction machine based on the updated parameter information; Determine the target tipping line based on the tipping line node information in the finite element model; For each of the target tipping lines, determine the stable nodes and tipping nodes based on the target tipping line and the updated parameter information to obtain a plurality of stable nodes and a plurality of tipping nodes; Determine the stability coefficient based on the plurality of stable nodes, the plurality of tipping nodes, and the target tipping line; 6. The tipping prediction method for a work machine according to claim 5, characterized in that, The determining the stability coefficient based on the plurality of stable nodes, the plurality of tipping nodes, and the target tipping line includes: Determine the first distance based on the relative position of the stable node and the target tipping line; Determine the sum of the first moments of all the stable nodes as the first stability moment, where the first moment is equal to the product of the first distance and the gravity of the stable node; Determine the second distance based on the relative position of the tipping node and the target tipping line; Determine the sum of the second moments of all the tipping nodes as the first tipping moment, where the second moment is equal to the product of the second distance and the gravity of the tipping node; Determine the ratio of the first stability moment to the first tipping moment as the stability coefficient; 7. The tipping prediction method for the construction machine according to claim 5, characterized in that, The determining the stability coefficient based on the plurality of stable nodes, the plurality of tipping nodes, and the target tipping line includes: When the moving speed of the working device of the construction machine is greater than the preset speed threshold, determine the first current position information and the first historical position information of the stable node based on a preset time interval, and determine the second current position information and the second historical position information of the tipping node; Determine the first acceleration of the stable node in the gravity direction based on the first current position information, the first historical position information, and the preset time interval; Determine the third distance based on the relative position of the stable node and the target tipping line; Determine the sum of the third moments of all the stable nodes as the second stability moment, where the third moment is equal to the product of the third distance and the first value, and the first value is the sum of the gravity of the stable node and the first acceleration; Determine the second acceleration of the tipping node in the gravity direction based on the second current position information, the second historical position information, and the preset time interval; Determine the fourth distance based on the relative position of the tipping node and the target tipping line; Determine the sum of the fourth moments of all the tipping nodes as the second tipping moment, where the fourth moment is equal to the product of the fourth distance and the second value, and the second value is the sum of the gravity of the tipping node and the second acceleration; Determine the ratio of the second stability moment to the second tipping moment as the stability coefficient; 8. The tipping prediction method for a work machine according to claim 1, characterized in that, The determining the tipping risk of the construction machine based on the target center of gravity and / or the stability coefficient includes: Determine the tipping risk based on the relative position of the target center of gravity and the target tipping line, where the target tipping line is determined based on the tipping line node information in the preset tipping mark information, and / or; Determine the tipping risk based on the stability coefficient and the preset level threshold.

9. The tipping prediction method for a work machine according to claim 8, characterized in that The determining the tipping risk based on the relative position of the target center of gravity and the target tipping line includes: When the distance between the target center of gravity and the target tipping line is less than the preset distance value, or when the target center of gravity is on the risk side of the target tipping line, it is determined that the working machine has a tipping risk; When the distance between the target center of gravity and the target tipping line is greater than the preset distance value and the target center of gravity is on the safe side of the target tipping line, it is determined that the working machine has no tipping risk; The determining the tipping risk based on the stability coefficient and the preset level threshold includes: Determine the risk level according to the stability coefficient and the preset level threshold; When the risk level is greater than or equal to the preset level, it is determined that the working machine has a tipping risk; When the risk level is less than the preset level, it is determined that the working machine has no tipping risk.

10. An overturning prediction device for a working machine, characterized in that, Including: A memory configured to store instructions; A processor configured to call the instructions from the memory and capable of implementing the working machine tipping prediction method according to any one of claims 1 to 9 when executing the instructions.

11. An earthmoving machine, characterized in that, Including: The working machine tipping prediction device according to claim 10.

12. A machine-readable storage medium, characterized in that, Instructions are stored on the machine-readable storage medium, and the instructions are used to cause the machine to execute the working machine tipping prediction method according to any one of claims 1 to 9.

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