Design method of a resilient product that can absorb and adapt to high-impact disturbances and has self-recovery performance

Abstract

The present invention belongs to the technical field of product design, and discloses a design method for a resilient product that can absorb and adapt to high-impact disturbances and has self-recovery performance. First, according to user requirements, the functions and structures of the product are determined; then more than one disturbance is introduced, and the functions and structures associated with the disturbance are extracted from the functions and structures of the product to construct a disturbance-structure-function failure network; then the functions prone to failure are determined; more than one resilient design factor is configured for the functions prone to failure; the functions prone to failure are combined with the selected resilient design factors to form updated functions; then, according to the updated function mapping, the structures prone to failure are updated. The present invention explains how high-impact disturbances restrict the design process and improves product resilience while minimizing their side effects.

Description

Technical Field

[0001] The present invention belongs to the technical field of product design, and relates to a design method for a resilient product that can absorb and adapt to high-impact disturbances and has self-recovery performance. Background Art

[0002] Driven by advanced information technology and artificial intelligence technology, products can more efficiently achieve different functions and meet the diverse needs of users. However, the increasingly large number of structures and the complex coupling relationships between components also make products more vulnerable to high-impact disturbances and face the risk of interruption. This has severely disrupted normal human production and life as well as the normal operation of products, causing serious economic losses and security consequences. Therefore, it is necessary to take corresponding measures to improve the ability of products to resist high-impact disturbances, solve structural and functional failures, and extend the service life of products.

[0003] To cope with failures and high-impact disturbances, many researchers mainly focus on developing highly reliable products through structural reinforcement optimization and maintenance. At the same time, resilience, as a new paradigm, endows products with the ability to absorb, adapt, recover, and learn, providing a new design idea for dealing with high-impact disturbances.

[0004] Patent inventions such as CN202011577019.4, CN201380047741.9, and CN201911077243.4 all deal with high-impact disturbances through predictive maintenance, mainly focusing on two aspects: equipment fault diagnosis and maintenance plan generation. The former uses machine learning algorithms to extract features from product operation data and information and train models to generate a product maintenance prediction model. The latter generates an optimal reliability maintenance plan under the constraints of limited resources and costs. Although maintenance methods such as corrective maintenance and predictive maintenance can restore products from failures, they have problems such as high cost, long time consumption, and even delay in work progress.

[0005] Patent invention CN202410285433.X discloses an anti-seismic resilience design method for medical buildings. By determining resilience goals, structural safety design, anti-seismic resilience design, post-earthquake function verification of buildings, and rapid function recovery, etc., it realizes that the building ensures that the structural safety degree meets the predetermined functions. However, it pays more attention to improving the reliability of medical buildings through structural reinforcement optimization measures and involves less in rapid function recovery strategies. Moreover, with the increase in natural disasters and the continuous increase of external and internal threats, even highly reliable products are prone to failure due to exceeding the safety threshold under high-impact and unforeseen disturbances. Summary of the Invention

[0006] In view of the above problems existing in the prior art, the present invention provides a design method for a resilient product that can absorb and adapt to high-impact disturbances and has self-recovery performance, aiming to solve the resilient product design scheme under constraints such as high-impact disturbances and evaluation objectives, which helps assist designers in carrying out resilient product design. While improving the product's ability to cope with high-impact disturbances, it meets user needs and ensures that product attributes fluctuate within an acceptable range, and provides support for the subsequent manufacturing, use, operation, and maintenance of resilient products.

[0007] The present invention considers the impact of high-impact disturbances on products and their design processes, and combines historical data to identify functional and structural failures, which can help designers better expand their understanding of the causes of failures and take measures against these high-impact disturbances or failures in subsequent designs, improving the product's ability to cope with high-impact disturbances. At the same time, the present invention also considers user satisfaction and product attributes, otherwise it will lead to unnecessary cost increases, damage user interests, and even affect the implementation of the final solution. Therefore, how to carry out failure analysis, take measures to improve product resilience, and seek a balance between user satisfaction and product attributes has become the core issue in constructing the resilient product design of the present invention.

[0008] Based on the above analysis, the present invention provides a design method for a resilient product that can absorb and adapt to high-impact disturbances and has self-recovery performance, which includes the following steps:

[0009] S1 Determine the functions and structures of the product according to user requirements;

[0010] S2 Introduce more than one disturbance, extract the functions and structures associated with the disturbance from the functions and structures of the product, and construct a disturbance-structure-function failure network;

[0011] S3 Determine the vulnerable functions according to the constructed disturbance-structure-function failure network; then divide the product functions into normal operation functions and vulnerable functions; configure more than one resilience design factor for the vulnerable functions; the vulnerable functions are combined with the selected resilience design factors to form updated functions;

[0012] S4 Divide the product structure into normal structure and vulnerable structure according to the constructed disturbance-structure-function failure network and the vulnerable functions; and update the vulnerable structure according to the updated function mapping;

[0013] S5 Combine the normal structure and the updated structure to obtain several resilient product design schemes.

[0014] In the above step S1, according to the user's requirements, several functions of the product are determined; a function is represented as the action of one structure on another structure; therefore, according to each function, the corresponding structure that meets the function can be determined, and this operation is to map from the function domain to the structure domain, and then construct a function-structure model. In the function-structure model, the edge between two structures represents the action between these two structures, that is, the function associated with these two structures. Conventional methods already disclosed in the art can be used to construct a function-structure model according to the user's requirements. For example, (① Functional analysis method, Dong, Y., Tan, R., Zhang, P., Peng, Q., & Shao, P. (2021). Product redesign using functional backtrack with digital twin. Advanced Engineering Informatics , 49 , 101361; ② Function-behavior-structure mapping method, Gero JS (1990) Design Prototypes: A Knowledge Representation Schema for Design. AI Magazine 11(4): 26–36).

[0015] In the above step S2, introducing perturbations (especially perturbations with high impact) in the function-structure model will cause damage to the structure, and then it is possible to quickly identify the affected function failures. Based on this, a perturbation-structure-function failure network can be constructed. The perturbation-structure-function failure network includes a perturbation layer, a structure layer, and a function failure layer; the perturbation layer includes more than one perturbation introduced; the structure layer includes the structures associated with the perturbation (that is, the mechanisms affected by the perturbation); the function failure layer includes the functions associated with the structures in the structure layer.

[0016] In the above step S3, according to the constructed perturbation-structure-function failure network, calculate the failure priority index, obtain the function failure ranking of the product; and according to the function failure ranking of the product, select several failure functions as vulnerable failure functions.

[0017] According to step S3, the product function is expressed as:

[0018] ;

[0019] In the formula, F i represents the normal operation function, i =1,2,..., n , n represents the number of normal operation functions; Represents the updated function after introducing the resilience design factor, x = 1, 2, ..., j , j represents the number of functions prone to failure, .

[0020] In the above step S4, according to the constructed perturbation-structure-functional failure network and functions prone to failure, the product structure is divided into a normal structure and a structure prone to failure, specifically:

[0021] ;

[0022] In the formula, represents the normal structure, i′ = 1, 2, ..., m , m represents the number of normally operating structures; represents the structure prone to failure, x′ = 1, 2, ..., j ′, j ′ represents the number of structures prone to failure.

[0023] According to the updated function mapping, the structure prone to failure is updated according to the following formula:

[0024] ;

[0025] ;

[0026] In the formula, DM represents the design matrix; represents the set of structures after updating the structure prone to failure; represents the set of updated functions; a mn represents and the mapping relationship of, when there is a mapping relationship, the corresponding a mn = 1, otherwise 0.

[0027] In the above step S5, the resilient product design scheme is expressed as:

[0028] ;

[0029] In the formula, represents the resilient product design scheme.

[0030] The above-mentioned resilient product design method that can absorb and adapt to high-impact perturbations and has self-recovery performance further includes steps:

[0031] S6 constructs the objective function and constraint conditions of cost, carbon emissions, and weight in the resilient product design scheme, and solves the constructed objective function to obtain candidate resilient design schemes.

[0032] Here, the cost, carbon emissions, and weight generated by the updated structure are mainly considered, and the objective function is:

[0033] ;

[0034] In the formula, represents the weight of the k th structure of the l th function; represents the raw material cost of the k th structure of the l th function; represents the design cost of the k th structure of the l th function; represents the processing cost of the k th structure of the l th function; represents the service cost of the k th structure of the l th function; represents the carbon emissions generated by raw material acquisition of the k th structure of the l th function; represents the carbon emissions generated by distribution of the k th structure of the l th function; represents the carbon emissions generated by processing of the k th structure of the l th function; represents the carbon emissions generated during use of the k th structure of the l th function; represents the carbon emissions at the end of the life cycle of the k th structure of the l th function; represents the volume of the k th structure of the l th function; represents the density of the k th structure of the l th function; K , L respectively represent the number of functions and the number of structures under the corresponding functions;

[0035] Constraint conditions:

[0036] ;

[0037] In the formula, , , respectively represent cost, carbon emissions, and maximum weight; represents the additional cost coefficient.

[0038] In a preferred implementation, the NSGA-II algorithm is used to solve the objective functions of cost, carbon emissions, and weight, and a Pareto solution set of candidate resilient product design schemes is obtained.

[0039] Compared with the prior art, the present invention has the following beneficial effects:

[0040] (1) The present invention considers the impact of high-impact disturbances on products and the impact of improving resilience on user needs and product attributes, and proposes a resilient product design method that can absorb and adapt to high-impact disturbances and has a self-recovery function, explains how high-impact disturbances restrict the design process, and improves product resilience while minimizing its side effects;

[0041] (2) In the design process of the method of the present invention, the ability of the product to cope with high-impact disturbances is improved from five aspects: absorption, adaptation, recovery, learning, and service, and the mapping relationship between structural failure and functional failure and the mapping relationship between functional adjustment and structural adjustment under high-impact disturbances are established through function backtracking;

[0042] (3) The present invention proposes key steps such as predictive fault analysis methods and solution configurations that integrate resilient design factors to solve the optimal resilient design scheme under high-impact disturbances, while taking into account user satisfaction and product attributes;

[0043] (4) Taking complex hole-making equipment as an example, the present invention uses predictive failure analysis methods and solution configurations that integrate resilient design factors to verify the effectiveness of the proposed design method, laying a foundation for the digitization and intelligentization of product design. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] The following gives a detailed explanation of the drawings in the specification.

[0045] Figure 1 is a schematic diagram of the resilient product design principle based on function backtracking;

[0046] Figure 2 is a schematic diagram of the process of the resilient product design method provided by the embodiment of the present invention, which can absorb and adapt to high-impact disturbances and has self-recovery performance;

[0047] Figure 3 is a conceptual design diagram of the hole-making equipment;

[0048] Figure 4For the product disturbance - function - structure model (a) and the disturbance - structure - function failure (DSFN) network (b) of the embodiments of the present invention;

[0049] Figure 5 is a Bayesian network;

[0050] Figure 6 For the pore - forming equipment disturbance - function - structure model of the embodiments of the present invention;

[0051] Figure 7 For the DSFN topological structure of the pore - forming equipment obtained based on the Bayesian network in the embodiments of the present invention;

[0052] Figure 8 For the updated structure of the function - adjustment - waiting mapping in the embodiments of the present invention;

[0053] Figure 9 For the candidate ductile design solutions obtained in the embodiments of the present invention. Specific embodiments

[0054] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of them. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts belong to the scope protected by the present invention.

[0055] To verify the effectiveness of the method of the present invention, the design process of the ductile pore - forming equipment is provided as a case in this embodiment. The pore - forming equipment is a complex equipment in industry that converts gravitational potential energy into kinetic energy to break rocks, and is widely used in the construction of transmission infrastructure such as tower racks and telegraph poles. With the development of ultra - high - voltage transmission level, higher requirements are also put forward for the supporting micro - pile holes. The field and underground environments are complex and unknown. In addition, the rock hardness increases with the increase of diameter and depth, and various high - impact disturbances increase the risk of drilling equipment failure. Therefore, the ductile design of the drilling machine not only ensures the efficiency and quality of pore - forming, but also improves the ability of the pore - forming equipment to cope with external interference.

[0056] This embodiment provides a ductile product design method that can absorb and adapt to high - impact disturbances and has self - recovery performance, as Figure 1 and Figure 2 shown, which includes the following steps:

[0057] S1 Determine the functions and structures of the product according to user requirements.

[0058] According to user requirements, determine several functions of the product. The function is expressed as the action of one structure on another structure, and the expression is shown in formula (1), that is, structure a through action Ai Act on the structure b 。

[0059] A i : Structure a → Structure b (1);

[0060] Therefore, according to each function, the corresponding structure that meets the function can be determined. This operation is also to map from the function domain to the structure domain, and then construct a function-structure model. In the function-structure model, the edge between two structures represents the action between these two structures, that is, the function associated with these two structures. Conventional methods already disclosed in the art can be used to construct a function-structure model according to user requirements. For example, ① functional analysis method, Dong, Y., Tan, R., Zhang, P., Peng, Q., & Shao, P. (2021). Product redesign using functional backtrack with digital twin. Advanced Engineering Informatics, 49, 101361 and ② function-behavior-structure mapping method, Gero JS (1990) Design Prototypes: A Knowledge Representation Schema for Design. AI Magazine 11(4): 26–36.

[0061] In this embodiment, according to the previous user requirement analysis and function-structure mapping, the functions and structures of the hole-forming equipment are determined, including functions required for excavation, traction, support, walking, fixing, driving, control, etc. The corresponding structure that meets the design requirements is selected as follows: grab bucket, wire rope, winch, main beam, support cylinder, oil tank, mast, crawler, boom bolt, hydraulic system, motor, remote controller, PLC, solenoid valve, as Figure 3 shown.

[0062] S2 Introduce more than one perturbation, extract the functions and structures associated with the perturbation from the functions and structures of the product, and construct a perturbation-structure-function failure network.

[0063] Introduce high-impact perturbations ( D i ) in the function-structure model, resulting in damage to the structure, and it is possible to quickly identify the affected function failures, as Figure 4 shown. For example D 1 causes a failure of Structure III, and the functions realized by Structures I, II, and V that are connected to Structure IIIA 1 , A 2 , A 3 , A 5 be affected, as shown in formula (2), represents the failure factor, represents the influence factor.

[0064] (2);

[0065] Extract the perturbations, affected structures and functions in the function model to construct a perturbation-structure-function failure network (DSFN); Therefore, the perturbation-structure-function failure network includes a perturbation layer, a structure layer and a function failure layer; The perturbation layer includes more than one introduced perturbation, which represents different perturbations generated by external environment, human factors, and internal product factors, denoted as D 1 , D 2 ,…, D i . The structure layer includes the structures associated with the perturbations (i.e., the mechanisms affected by the perturbations). Under the action of high-impact perturbations, product performance degradation or structural failure occurs, denoted as S a1 , S a2 ,…, S an . The function failure layer includes the functions associated with the structures in the structure layer. In the function failure layer, the product may not be able to perform its expected functions under the influence of structural failure, denoted as F f1 , F f2 ,…, F fn . The directed edges represent the failure causal relationships between the three layers.

[0066] In this embodiment, for the above-mentioned hole-forming equipment, three types of high-impact perturbations are considered, namely hard rocks, uneven surfaces such as mud, gravel and highlands, and alternating loads caused by repeated impacts. When excavating hard rocks, such as granite, the grab teeth may wear or even break. Repeated impacts on the ground will cause periodic load changes in the drill rig, resulting in failures such as wear and breakage of the wire rope, deformation and breakage of the mast, and loosening and breakage of the boom bolts. Walking on soil, gravel and uneven surfaces may cause track wear and breakage. The above structural failures will affect the execution of the corresponding functions, resulting in function failures.

[0067] Utilize the above-mentioned high-impact perturbations, structural failures, and functional failures to construct a perturbation-functional model and a DSFN network, as Figure 6 , 7 shown. For Figure 7 , yes represents the occurrence probability, and no represents the non-occurrence probability; specifically, it is calculated based on the statistical data corresponding to the faults generated during the actual operation of the grab equipment or estimated by expert experience; given the probability of the bottom-layer nodes and the probability of the upper-layer nodes occurring under the condition of the occurrence of the bottom-layer nodes, the probability of the upper-layer nodes occurring can be solved using the total probability formula.

[0068] S3 Based on the constructed perturbation-structural-functional failure network, determine the failure-prone functions; then divide the product functions into normal operation functions and failure-prone functions; configure more than one resilience design factor for the failure-prone functions; combine the failure-prone functions with the selected resilience design factors to form updated functions.

[0069] For the topological structure of the DSFN network, the Failure Priority Index (FPI) is used to measure the severity of functional failures from multiple dimensions of severity (S), occurrence probability (P), and detectability (D), so as to give priority to these failure-prone functions in the subsequent design process, as shown in formula (3). The occurrence probability refers to the frequency of failures occurring within the reliability and service life of the product, and is solved using the Bayesian network, expressed as a conditional probability. For example, the failure probability of structure B under high-impact perturbation A, and the failure probability of function C when structure B fails. Taking Figure 5 as an example, calculate the probability P(B) of structure B failing. Using the total probability formula, the probability P(A n ) of each parent node (high-impact perturbation) A n occurring is multiplied by the probability P(B|A n ) of structure B failing under the condition of the occurrence of each parent node A n ), that is, formula (4). When it is necessary to solve the posterior probability, that is, the probability P(A n |B) of event A n occurring when structure B fails, as shown in formula (5), only P(B|A n ) and P(A n ) need to be known to obtain it. P(B|A n ) and P(A n ) can be obtained by recording the number of historical product failures. The severity (S) describes the degree of structural failure and its impact on other structures of the product. The detectability (D) describes the possibility of detecting a fault. The severity and detectability are respectively assigned values by experts according to experience and the degree of attention to the indicators.

[0070] (3);

[0071] (4);

[0072] (5).

[0073] Therefore, according to the calculated failure priority index, obtain the functional failure ranking of the product; and select several failure functions as the vulnerable failure functions according to the functional failure ranking of the product.

[0074] In this embodiment, Bayes' theorem is used to calculate the occurrence probability of functional failure. The occurrence probabilities of failure of "driving function", "support function", "traction function", "fixing function", and "walking function" can be calculated as 0.68, 0.35, 0.52, 0.33, and 0.26 respectively. Experts gave the scores of the severity and detectability of different functional failures. According to Equation (3), the FPI value and its ranking, compared with other faults, the risk management of the drilling and traction functions of the drill needs more attention, as shown in Table 1. Thus, the product functions are divided into normal operation functions F i and vulnerable failure functions F x .

[0075] Table 1 Functional failure ranking of the drill

[0076]

[0077] For the vulnerable failure functions solved for the disturbance-structure-functional failure network F x , five resilience design factors y are defined, namely absorption, adaptation, recovery, learning, and service, for function adjustment. The product function is expressed as shown in Equation (6). F i represents the function of normal operation. Combining the selected resilience design factors with the vulnerable failure functions gives the updated function after introducing the resilience design factors, that is , which is used to enhance the ability of these vulnerable failure functions to cope with high-impact disturbances.

[0078] (6);

[0079] In the formula, F i represents the function of normal operation, i = 1, 2, ..., n , n represents the number of functions of normal operation; represents the updated function after introducing the resilience design factors, x = 1, 2, ..., j , j represents the number of vulnerable failure functions, 。

[0080] To cope with functional failures, five resilience design factors are defined, namely absorption, adaptation, recovery, learning, and service. Combined with the failed function, they constitute the renewal function. The concepts of specific resilience design factors are as follows:

[0081] Absorption is the inherent ability of a product to withstand and attenuate the continuous impact of high-impact disturbances on product performance and minimize the consequences of the disturbances. The product can make preparations in advance and make corresponding adjustments by strengthening weak links of the product, product upgrades, regular maintenance, etc. At the same time, by improving the independence between structures, cascading failures can be minimized, and corresponding buffers can be set and controlled within critical thresholds.

[0082] Adaptation reflects the product's ability to identify high-impact disturbances, predict possible failures, continue to operate in the event of an interruption, and optimize the recovery plan based on the discovery of the interruption event, especially when the absorption capacity has been exceeded. Specifically, it can be achieved in the following ways: (1) Monitoring the product status and external environment through sensors; (2) Predicting product weaknesses, remaining service life, and possible failures based on monitored performance data; (3) Assigning the authority to prioritize tasks during a crisis; (4) Flexibly changing the product configuration; (5) Improving the product's coordination or control ability; sensors and communication algorithms are used to enhance internal interactions between components.

[0083] Recovery refers to the ability to restore the product to an acceptable state, which meets the operation requirements through structural and functional redundancy. Structural redundancy means using a pre-designed backup structure, i.e., redundant resources, to replace the damaged structure. Functional redundancy means training structures with similar functions to restore the target component to the desired state.

[0084] Learning describes the ability to learn from previous high-impact disturbances by collecting and analyzing event, crisis, and accident data, as well as deep learning, improving its procedures, reconfiguring structures and recovery actions, preparing for future known and possible similar disturbances, and further enhancing its response to high-impact disturbances or failures. The improvement of learning ability can be carried out in several aspects: (1) Active learning and passive learning; active learning means monitoring the execution of the product's work and learning from the gap between the work imagined in the design stage and the actual work; passive learning refers to learning from the changes and failures that have occurred; (2) Data sharing, in addition to historical data and experience, fault data between products can be transmitted across organizational boundaries; for example, if a product has a structural failure under the action of bad weather, another product learns from the fault data of this product and adjusts its structure and function accordingly to cope with this high-impact disturbance; (3) Product adjustment, iteratively testing and reconfiguring the recovery solution based on the learning results.

[0085] Due to technical limitations, it is difficult for the product to independently cope with all high-impact interferences. The role of the service becomes prominent in three main aspects: (1) providing the resources required by the product. During the process of handling failures, the resources of the product, such as redundancy and power, will be consumed, and these resources are replenished by humans; (2) providing maintenance services. Predictive maintenance (predicting faults based on monitoring data and giving corresponding measures) is to maintain the health state of the system and prevent faults from occurring; in addition, corrective maintenance is carried out to restore the functions of faulty components or subsystems; (3) strategic decision-making. When the product is interfered with, humans can quickly adopt strategies to restore the faulty product with limited resources.

[0086] S4 divides the product structure into a normal structure and a failure-prone structure according to the constructed disturbance-structure-functional failure network and the failure-prone functions; and updates the failure-prone structure according to the updated function mapping.

[0087] According to the disturbance-structure-functional failure network, the structure (S) of the product can be divided into a normal structure ( ) and a failure-prone structure ( ). Remap the new functions to the structural domain to adjust the failure-prone structure. The new functions form an updated function set , and the improved structure also forms a set of updated structures of the failure-prone structure . The mapping relationship between the two sets is represented by the design matrix [DM], as shown in the following equations (7)-(9).

[0088] (7);

[0089] In the formula, represents the normal structure, i′ = 1, 2, ..., m , m represents the number of normal operating structures; represents the failure-prone structure, x′ = 1, 2, ..., j ′, j ′ represents the number of failure-prone structures.

[0090] (8);

[0091] (9);

[0092] In the formula, DM ] represents the design matrix; represents the set of structures after updating the failure-prone structure; represents the updated function set; a mn represents The mapping relationship with When there is a mapping relationship, the corresponding a mn = 1, otherwise 0.

[0093] For example, for the grab of the hole-forming equipment (corresponding to the tunneling function), the design matrix between the update function and the update structure is as follows:

[0094] .

[0095] In this embodiment, for the design of the hole-forming equipment, a ductile design factor is configured for the function prone to failure, and according to the new function formed after the function adjustment, it is further mapped back to the structural domain to adjust the structure prone to failure, and finally a new improved structure is obtained, as Figure 8 shown.

[0096] S5 combines the normal structure and the updated structure to obtain several ductile product design schemes.

[0097] The ductile product design scheme is expressed as:

[0098] (10);

[0099] In the formula, represents the ductile product design scheme.

[0100] In this embodiment, in the design of the hole-forming equipment, for the same type of function failure, the newly formed structures are randomly combined to form an updated structure, and the normal structure and the updated structure are combined to obtain a ductile product design scheme for subsequent scheme configuration.

[0101] S6 constructs the objective function and constraint conditions of cost, carbon emission and weight in the ductile product design scheme, and solves the constructed objective function to obtain candidate ductile design schemes.

[0102] The obtained structure set is combined to configure different ductile design schemes. During the configuration process, it is necessary to consider whether the cost, environment, and product attributes are affected. In the present invention, cost, weight, and carbon emission are introduced as the constraint conditions for configuring the ductile design scheme, representing the requirements for product budget, lightweight, and environmental factors, and the NSGA-II algorithm is used for solving to obtain a trade-off scheme that minimizes product carbon emission, cost, and weight.

[0103] Here, mainly consider the cost, carbon emission and weight generated by the updated structure, and the objective function is:

[0104] (11);

[0105] In the formula, represents the kThe weight of the l structure of the function; k The raw material cost of the l structure of the function; k The design cost of the l structure of the function; k The processing cost of the l structure of the function; k The service cost of the l structure of the function; k The carbon emissions generated from raw material acquisition of the l structure of the function; k The carbon emissions generated from distribution of the l structure of the function; k The carbon emissions generated from processing of the l structure of the function; k The carbon emissions generated from use of the l structure of the function; k The carbon emissions generated at the end of the life cycle (i.e., post - processing) of the l structure of the function; k The volume of the l structure of the function; k The density of the l structure of the K , L respectively represent the number of functions and the number of structures under the corresponding functions;

[0106] Constraints:

[0107] (12);

[0108] In the formula, , , respectively represent the maximum values of cost, carbon emissions, and weight; represents the additional cost coefficient, such as factors not considered in operations, supply chain management, environment, etc.

[0109] Cost considerations mainly include expenditures related to raw material procurement, design, manufacturing, and services. Weight refers to the cumulative weight of the structure after all components are assembled. Carbon emissions mainly measure the carbon footprint throughout the product's life cycle, which is divided into five different stages: raw material acquisition, manufacturing and assembly, distribution, use, and end of life. In terms of constraints, each optimization objective must not exceed a certain value; only one structural variant can be selected for each type of structure (corresponding to the last term in Equation (12) above). Finally, through the non-dominated sorting and calculation of crowding distance of the NSGA-II algorithm, the Pareto solution set of candidate resilient design solutions is obtained.

[0110] In this embodiment, the costs, carbon emissions, and weights of the updated structures are calculated respectively, as shown in Table 2. Based on the mathematical model established by Equations (11)-(12), and the NSGA-II optimization algorithm is used for calculation. Finally, candidate resilient design solutions are obtained, as Figure 9 shown.

[0111] Table 2 Updated Structures of Hole-making Equipment

[0112]

[0113] Compared with other alternatives, Solution 1 (i.e., M in Table 2 above 抓斗 5 +M 钢丝绳 3 +M 桅杆 2 +M 履带 7 + M 螺栓 3The structural set) stands out among other solutions with its lower cost and weight, meeting user needs by performing its functions while enhancing product toughness. For all functional failures, Solution 1 conducts predictive maintenance, capable of predicting structural failures in advance and taking corresponding measures to minimize the economic burden on users. For excavation functional failures, when the grab arm breaks as detected by the triaxial inclinometer and tension sensor, the control center drives the motor to retract the broken grab arm, and the remaining three grab arms continue to work. For traction functional failures, under the same cyclic load, multi-rope linkage is used instead of a single wire rope to reduce wear. The tension sensor is used to detect whether the wire rope breaks, discovers abnormal tension in a timely manner by learning the tension data, and predicts the possible break time of the wire rope through the learning module. For support function damage, reinforcing ribs are used to enhance the mast's ability to resist cyclic overturning moments, and strain gauges are used to monitor whether the mast breaks. For crawler walking functional failures, displacement, vibration sensors, and a learning module are used to monitor and predict whether the crawler is worn or damaged. If the crawler is damaged, due to the complexity of the crawler itself, the damaged part of the crawler is replaced manually. For fixing functional failures, Nord-lock bolts are used to absorb cyclic loads and prevent the boom bolts from loosening, and the damaged boom bolts are replaced manually. In short, Solution 1 can improve product toughness while meeting user needs within an acceptable cost, carbon emissions, and weight range, as Figure 9 shown.

[0114] Those of ordinary skill in the art will realize that the embodiments here are to help readers understand the principles of the present invention, and it should be understood that the protection scope of the present invention is not limited to such specific statements and embodiments. Those of ordinary skill in the art can make various other specific deformations and combinations without departing from the essence of the present invention based on the technical revelations disclosed in the present invention, and these deformations and combinations are still within the protection scope of the present invention.

Claims

1. A method for designing a tough product that can absorb and adapt to high-impact disturbances and has self-recovery performance, characterized in that: The following steps are involved: S1Determine the function and structure of the product based on user needs; S2 introduces more than one disturbance, extracts the functions and structures associated with the disturbance from the functions and structures of the product, and constructs a disturbance-structure-function failure network; S3 determines the prone-to-failure functions based on the constructed disturbance-structure-function failure network; and then divides the product functions into normal operating functions and prone-to-failure functions; Assign more than one toughness design factor to failure-prone functions; The failure-prone function is combined with the selected toughness design factor to form the renewal function; S4 divides the product structure into a normal structure and a failure-prone structure based on the constructed disturbance-structure-function failure network and the failure-prone function; and updates the failure-prone structure based on the update function mapping to obtain an updated structure; S5 combines the normal structure with the updated structure to obtain several tough product design solutions.

2. The method for designing a tough product capable of absorbing and adapting to high-impact disturbances and having self-recovery performance according to claim 1, characterized in that: In step S2, the disturbance-structure-functional failure network includes a disturbance layer, a structure layer and a functional failure layer; the disturbance layer includes one or more disturbances introduced; the structure layer includes a structure associated with the disturbance; and the functional failure layer includes a function associated with the structure of the structure layer.

3. The method for designing a tough product capable of absorbing and adapting to high-impact disturbances and having self-recovery performance according to claim 1, characterized in that: In step S3, based on the constructed disturbance-structure-function failure network, the failure priority index is calculated to obtain the functional failure ranking of the product; and according to the functional failure ranking of the product, several failure functions are selected as prone to failure functions.

4. The method for designing a tough product capable of absorbing and adapting to high-impact disturbances and having self-recovery performance according to claim 3, characterized in that: According to step S3, the product function is expressed as: ； In the formula, F i Indicates normal operating function, i =1,2,..., n , n Indicates the number of normal operating functions; represents the updated function after introducing the toughness design factor, x =1,2,..., j , j Indicates the number of functions that are prone to failure, .

5. The method for designing a tough product capable of absorbing and adapting to high-impact disturbances and having self-recovery performance according to claim 4, characterized in that: In step S4, the product structure is divided into a normal structure and a failure-prone structure according to the constructed disturbance-structure-function failure network and the failure-prone function, specifically: ； In the formula, Represents a normal structure, i′ =1,2,..., m , m Indicates the number of normal operating structures; represents a failure-prone structure, x′ =1,2,..., j ′, j ′ represents the number of structures susceptible to failure.

6. The method for designing a tough product capable of absorbing and adapting to high-impact disturbances and having self-recovery performance according to claim 5, characterized in that: According to the update function mapping, the vulnerable structure is updated according to the following formula: ； ； In the formula, [ DM ] represents the design matrix; represents the set of structures after the failure-prone structures are updated; Represents a collection of update functions; a mn express and The mapping relationship, when there is a mapping relationship, the corresponding a mn =1 if the value is set to 0, otherwise it is 0.

7. The method for designing a tough product capable of absorbing and adapting to high-impact disturbances and having self-recovery performance according to claim 6, characterized in that: In step S5, the toughness product design solution is expressed as: ； In the formula, Represents a resilient product design.

8. The method for designing a tough product capable of absorbing and adapting to high-impact disturbances and having self-recovery performance according to any one of claims 1 to 7, characterized in that: Also includes the steps: S6 constructs the objective functions and constraints of cost, carbon emissions and weight in the resilient product design scheme, and solves the constructed objective functions to obtain candidate resilient design schemes.

9. The method for designing a tough product capable of absorbing and adapting to high-impact disturbances and having self-recovery performance according to claim 8, characterized in that: The objective function for cost, carbon emissions and weight in building a resilient product design is: ； In the formula, Indicates k Function l The weight of each structure; Indicates k Function l The raw material cost of each structure; Indicates k Function l Design cost of each structure; Indicates k Function l The processing cost of each structure; Indicates k Function l The service cost of each structure; Indicates k Function l Carbon emissions from the acquisition of structural raw materials; Indicates k Function l Carbon emissions generated by the distribution of each structure; Indicates k Function l Carbon emissions from processing of each structure; Indicates k Function l Carbon emissions from the use of each structure; Indicates k Function l Carbon emissions generated at the end of the life cycle of each structure; Indicates k Function l The volume of a structure; Indicates k Function l The density of the structure; K , L They represent the number of functions and the number of structures under the corresponding functions respectively; Constraints: ； In the formula, , , They represent the maximum values ​​of cost, carbon emission and weight respectively; Represents the additional cost factor.

10. The method for designing a tough product capable of absorbing and adapting to high-impact disturbances and having self-recovery performance according to claim 9, characterized in that: The NSGA-Ⅱ algorithm is used to solve the objective functions of cost, carbon emission and weight, and the Pareto solution set of candidate toughness product design schemes is obtained.

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