Design method of tough product capable of absorbing and adapting to high influence disturbance and having self-recovery performance

Abstract

The invention belongs to the technical field of product design, and discloses a method for designing a tough product capable of absorbing and adapting to high influence disturbance and having self-recovery performance, which comprises the following steps of: firstly, determining the function and the structure of the product according to user requirements; introducing more than one disturbance, extracting functions and structures associated with the disturbance from functions and structures of the product, and constructing a disturbance-structure-function failure network; determining an easy-to-fail function; configuring more than one toughness design factor for the easy-to-fail function; combining the easy-to-fail function with the selected toughness design factor to form an updating function; and updating the easy-to-fail structure according to the update function mapping. The method explains how the high-influence disturbance restricts the design process, and improves the product toughness while reducing the side effects to the maximum extent.

Description

Technical Field

[0001] The present invention belongs to the technical field of product design, and relates to a method for designing a tough 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 realize different functions more efficiently and meet the diverse needs of users. However, the increasing number of structures and the complex coupling relationship between components also make products more vulnerable to high-impact disturbances and face the risk of interruption. This seriously disrupts the normal production and life of humans and the normal operation of products, causing serious economic losses and safety 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] In order to cope with failures and high-impact disturbances, many researchers mainly focus on developing products with high reliability through structural reinforcement optimization and maintenance. At the same time, resilience, as a new paradigm, gives products the ability to absorb, adapt, recover, and learn, providing a new design idea for coping with high-impact disturbances.

[0004] Invention patents CN202011577019.4, CN201380047741.9, CN201911077243.4, etc., all deal with high-impact disturbances through predictive maintenance, mainly focusing on equipment fault diagnosis and maintenance plan generation. The former uses machine learning algorithms to extract features and train models of product operation data and information to generate product maintenance prediction models. The latter generates maintenance plans with optimized reliability under the constraints of limited resources and costs. Although corrective maintenance, predictive maintenance and other maintenance methods can be used to recover products from failures, they are costly, time-consuming, and may even delay work progress.

[0005] Invention patent CN202410285433.X discloses a seismic resilience design method for medical buildings. By determining resilience targets, structural safety design, seismic resilience design, building post-earthquake function verification, and rapid functional recovery, the building is able to ensure that the structural safety meets the predetermined functions. However, it focuses more on improving the reliability of medical buildings through structural reinforcement optimization measures, and involves less rapid functional recovery strategies. Moreover, with the increase in natural disasters and the continued increase in external and internal threats, even products designed for high reliability are prone to failure due to exceeding the safety threshold under high impact and unforeseen interference. Summary of the invention

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

[0007] The present invention takes into account the impact of high-impact disturbances on products and their design processes, and combines historical data to identify functional and structural faults, which can help designers better expand their understanding of the causes of failures, and take measures to deal with these high-impact interferences or failures in subsequent designs, thereby improving the product's ability to cope with high-impact disturbances. At the same time, the present invention also takes into account 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 conduct failure analysis, take measures to improve product resilience, and seek a balance between user satisfaction and product attributes have become the core issues of the present invention in constructing resilient product design.

[0008] Based on the above analysis, the present invention provides a design method for a tough product that can absorb and adapt to high-impact disturbances and has self-recovery performance, which includes the following steps: 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 function based on the constructed disturbance-structure-function failure network; further divides the product function into normal operation function and prone-to-failure function; configures one or more toughness design factors for the prone-to-failure function; the prone-to-failure function is combined with the selected toughness design factor to form an update function; S4 divides the product structure into normal structure and failure-prone structure based on the constructed disturbance-structure-function failure network and failure-prone functions; and updates the failure-prone structure based on the update function mapping; S5 combines the normal structure with the updated structure to obtain several tough product design solutions.

[0009] In the above step S1, several functions of the product are determined according to user needs; the function is expressed as the effect of one structure on another structure; therefore, according to each function, the corresponding structure that satisfies 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 the two structures represents the effect between the two structures, that is, the function associated with the two structures. The function-structure model can be constructed according to user needs by using conventional methods disclosed in the art, 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;②Function-behavior-structure mapping method, Gero JS (1990) Design Prototypes: A Knowledge Representation Schemafor Design. AI Magazine 11(4): 26–36).

[0010] In the above step S2, introducing disturbances (especially disturbances with high impact) into the function-structure model will cause damage to the structure, thereby enabling rapid identification of the affected functional failures. Based on this, a disturbance-structure-functional failure network can be constructed. 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 introduced disturbances; the structure layer includes a structure associated with the disturbance (i.e., a mechanism affected by the disturbance); and the functional failure layer includes functions associated with the structure of the structure layer.

[0011] In the above 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.

[0012] 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, .

[0013] In the above 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.

[0014] 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 updated structure set of vulnerable structures; 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.

[0015] In the above step S5, the toughness product design solution is expressed as: ; In the formula, Represents a resilient product design.

[0016] The above-mentioned method for designing a resilient product capable of absorbing and adapting to high-impact disturbances and having self-recovery performance also includes the steps of: 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.

[0017] Here we mainly consider the cost, carbon emissions and weight of the updated structure, and the objective function is: ; In the formula, Indicates kFunction 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.

[0018] In the preferred implementation, the NSGA-Ⅱ algorithm is used to solve the objective functions of cost, carbon emission and weight to obtain the Pareto solution set of candidate toughness product design schemes.

[0019] Compared with the prior art, the present invention has the following beneficial effects: (1) This paper 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 self-recovery functions. It explains how high-impact disturbances constrain the design process and improves product resilience while minimizing its side effects. (2) During the design process, the method of the present invention improves the product's ability to cope with high-impact disturbances from five aspects: absorption, adaptation, recovery, learning, and service. Through functional backtracking, 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; (3) The present invention proposes key steps such as predictive failure analysis method and scheme configuration integrating resilience design factors to solve the optimal resilience design scheme under high impact disturbance while taking into account user satisfaction and product attributes; (4) Taking complex hole-making equipment as an example, the present invention uses a predictive failure analysis method and a solution configuration that integrates toughness design factors to verify the effectiveness of the proposed design method, laying the foundation for the digitalization and intelligence of product design. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] The following is a detailed explanation of the drawings in the specification.

[0021] Figure 1 This is a schematic diagram of the design principle of resilient products based on functional backtracking; Figure 2 A schematic flow chart of a method for designing a resilient product that can absorb and adapt to high-impact disturbances and has self-recovery performance provided by an embodiment of the present invention; Figure 3 This is a conceptual design drawing of the hole-forming equipment; Figure 4 The disturbance-function-structure model (a) and the disturbance-structure-function failure (DSFN) network (b) of the product of the embodiment of the present invention are shown; Figure 5 is a Bayesian network; Figure 6 A disturbance-function-structure model of a hole-forming device according to an embodiment of the present invention; Figure 7 The DSFN topology structure of the hole forming equipment obtained based on the Bayesian network in the embodiment of the present invention; Figure 8 To adjust the update structure of candidate mapping for the embodiment of the present invention; Fig. 9 This is a candidate toughness design solution obtained by an embodiment of the present invention. DETAILED DESCRIPTION

[0022] The following will clearly and completely describe the technical solutions of various embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0023] In order to verify the effectiveness of the method of the present invention, this embodiment provides a tough hole-drilling equipment design process as a case. Drilling equipment is a complex equipment in industry that converts gravitational potential energy into kinetic energy to achieve rock crushing. It is widely used in the construction of power transmission infrastructure such as towers and poles. With the development of ultra-high voltage power transmission levels, higher requirements are also placed on the supporting micro-pile holes. The field and underground environment are complex and unknown, and the hardness of the rock increases with the increase of diameter and depth. Various high-impact disturbances increase the risk of drilling equipment failure. Therefore, the toughness design of the drilling machine not only ensures the efficiency and quality of the hole, but also improves the ability of the drilling equipment to deal with external interference.

[0024] This embodiment provides a design method for a resilient product that can absorb and adapt to high-impact disturbances and has self-recovery performance. Figure 1 and Figure 2 As shown, it includes the following steps: S1 Determine the function and structure of the product based on user needs.

[0025] According to user needs, several functions of the product are determined. Function is expressed as the effect of one structure on another structure, as shown in formula (1), that is, structure a Through Action A i Acting on the structure b .

[0026] A i :structure a →Structure b (1); Therefore, according to each function, the corresponding structure that satisfies the function can be determined. 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 the two structures represents the interaction between the two structures, that is, the function associated with the two structures. The function-structure model can be constructed according to user needs by using conventional methods disclosed in the art, such as 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.

[0027] In this embodiment, the functions and structures of the hole-forming equipment are determined based on the previous user demand analysis and functional structure mapping, including the required functions of digging, traction, support, walking, fixing, driving, and control. The corresponding structures that meet the design requirements are selected as follows: grab, wire rope, winch, main beam, support cylinder, oil tank, mast, crawler, boom bolt, hydraulic system, motor, remote control, PLC, solenoid valve, etc. Figure 3 shown.

[0028] 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.

[0029] Introducing high-impact perturbations into the functional-structural model ( D i ), resulting in structural damage, can quickly identify the affected functional failures, such as Figure 4 For example D 1 Causes the failure of structure III, and the functions realized by structures I, II, and V that are related to structure III A 1. A 2. A 3. A 5 is affected, as shown in formula (2), represents the failure factor, Represents the impact factor.

[0030] (2); The disturbance, affected structure and function in the functional model are extracted to construct a disturbance-structure-function failure network (DSFN); therefore, the disturbance-structure-function failure network includes a disturbance layer, a structure layer and a function failure layer; the disturbance layer includes one or more disturbances introduced, which represent different disturbances caused by the external environment, human factors and internal factors of the product, denoted as D 1, D 2, ..., D i The structural layer includes the structure associated with the disturbance (i.e., the mechanism affected by the disturbance). Under the high-impact disturbance, product performance degradation or structural failure occurs, which is recorded as S a1 , S a2 , …, S an The functional failure layer includes functions associated with the structure of the structural layer. In the functional failure layer, the product may not be able to perform the expected function under the influence of structural failure, which is recorded as F f1 , F f2 , …, F fn The directed edges represent the causal relationship of failure among the three layers.

[0031] In this embodiment, three types of high-impact disturbances are considered for the above-mentioned hole-making equipment, namely, hard rock, uneven surfaces such as mud, gravel and high ground, and alternating loads caused by repeated impacts. When digging hard rocks, such as granite, the grab teeth may wear or even break. Repeated impacts on the ground can cause periodic load changes in the drilling rig, leading to failures such as wear and breakage of the wire rope, deformation and breakage of the mast, loosening and breakage of the boom bolts, etc. Walking on mud, gravel and uneven surfaces may cause wear and breakage of the crawler tracks. The above-mentioned structural failures will affect the execution of the corresponding functions and cause functional failure.

[0032] The above high-impact disturbances, structural failures, and functional failures are used to construct disturbance-function models and DSFN networks, such as Figure 6 , 7 As shown. Figure 7 In the formula, yes indicates the probability of occurrence, and no indicates the probability of non-occurrence. Specifically, the probability is calculated based on the statistical data corresponding to the faults generated in the actual operation of the grab equipment or estimated by expert experience. Given the probability of the bottom node and the probability of the upper node occurring under the condition of the bottom node occurring, the total probability formula can be used to solve the probability of the upper node occurring.

[0033] S3 determines the failure-prone functions based on the constructed disturbance-structure-function failure network; then divides the product functions into normal operation functions and failure-prone functions; configures one or more resilience design factors for the failure-prone functions; and combines the failure-prone functions with the selected resilience design factors to form an update function.

[0034] For the topology of the DSFN network, the Failure Priority Index (FPI) is used to measure the severity of functional failures from multiple dimensions, including severity (S), probability of occurrence (P), and detectability (D), so that these prone-to-failure functions can be given priority in the subsequent design process, as shown in Formula (3). The probability of occurrence refers to the frequency of failure within the reliability and service life of the product. It is solved using a Bayesian network and expressed as a conditional probability, such as the failure probability of structure B under high-impact disturbance A, and the failure probability of function C when structure B fails. Figure 5 For example, calculate the probability P(B) of failure of structure B. Using the total probability formula, each parent node (high impact disturbance) A n The probability of occurrence P (A n ) with each parent node A n The probability of failure of structure B under the occurrence condition P(B|A n ) multiplied by the formula (4). When the posterior probability needs to be solved, that is, when the B structure fails, A n The probability of an event occurring is P(A n |B), as in formula (5), we only need to know P(B|A n ), P(A n ) can be obtained, P(B|A n ), P(A n ) can be obtained by recording the number of historical product failures. Severity (S) describes the degree of structural failure and its impact on other product structures. Detection (D) describes the possibility of detecting a failure. Severity and detection are assigned by experts based on their experience and the degree of attention to the indicators.

[0035] (3); (4); (5).

[0036] Therefore, according to the calculated failure priority index, the functional failure ranking of the product is obtained; and according to the functional failure ranking of the product, several failure functions are selected as prone to failure functions.

[0037] In this embodiment, the Bayesian theorem is used to calculate the probability of functional failure. The failure probabilities of "excavation function", "support function", "traction function", "fixation function" and "walking function" can be calculated to be 0.68, 0.35, 0.52, 0.33 and 0.26 respectively. Experts gave scores for the severity and detectability of different functional failures. According to formula (3), FPI values ​​and their rankings, compared with other faults, the risk management of drilling rig excavation and traction functions requires more attention, as shown in Table 1. Thus, the product functions are divided into normal operation functions. F i and easy failure function F x .

[0038] Table 1. Ranking of functional failures of drilling rigs

[0039] Failure-prone functions solved for perturbation-structural-functional failure networks F x , five resilience design factors y are defined, namely absorption, adaptation, recovery, learning and service, which are used for functional adjustment. The product function is expressed as shown in formula (6). F i The selected toughness design factor is combined with the failure-prone function, and the updated function after the toughness design factor is introduced is given as , used to enhance the ability of these vulnerable functions to cope with high-impact disturbances.

[0040] (6); 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, .

[0041] In order to deal with functional failure, five resilience design factors are defined, namely absorption, adaptation, recovery, learning and service. Combined with the failure function, they constitute the update function. The concepts of specific resilience design factors are as follows: 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 disturbances. Products can be prepared in advance and make corresponding adjustments by strengthening product weaknesses, product upgrades, regular maintenance, etc. At the same time, improving the independence between structures can minimize cascading failures and set corresponding buffers to control within critical thresholds.

[0042] Adaptability reflects the ability of a product to identify high-impact disturbances, predict possible failures, continue to operate under disruptions, and optimize recovery plans based on the discovery of disruptions, especially when the absorptive capacity has been exceeded. Specifically, it can be achieved in the following ways: (1) monitoring of product status and external environment through sensors; (2) prediction of product weaknesses, remaining service life, and possible failures based on monitoring performance data; (3) authority to assign task priorities in times of crisis; (4) flexible changes in product configuration; (5) improved product coordination or control capabilities; sensors and communication algorithms are used to enhance internal interactions between components.

[0043] Recovery is the ability to restore a product to an acceptable state that meets operational requirements through structural and functional redundancy. Structural redundancy refers to the use of pre-designed backup structures, i.e., redundant resources, to replace damaged structures. Functional redundancy refers to restoring the target component to the desired state by training structures with similar functions.

[0044] Learning describes the ability to learn from previous high-impact disruptions, improve its procedures, reconfigure structure and recovery actions, prepare for future known and possible similar disruptions, and further improve its response to high-impact disruptions or failures by collecting and analyzing event, crisis and accident data and deep learning. The improvement of learning capabilities can be carried out in several ways: (1) active learning and passive learning; active learning means monitoring the performance of product work and learning from the gap between the work imagined in the design stage and the actual work; passive learning means learning from changes and failures that have already occurred; (2) data sharing, in addition to historical data and experience, failure data between products can be transferred across organizational boundaries; for example, if a product suffers a structural failure due to severe weather, another product learns from the failure data of this product and adjusts its structure and function accordingly to cope with this high-impact disruption; (3) product adjustment, iteratively testing and reconfiguring recovery solutions based on learning results.

[0045] Due to technical limitations, it is difficult for products to independently handle all high-impact disturbances. The role of services becomes prominent in three main aspects: (1) Providing the resources required by products. In the process of handling failures, the resources of products, such as redundancy and power, are consumed, and these resources are replenished by humans; (2) Providing maintenance services. Predictive maintenance (predicting failures based on monitoring data and giving corresponding measures) is to maintain the health of the system and prevent failures; in addition, corrective maintenance is performed to restore the function of faulty components or subsystems; (3) Strategic decision-making. When products are disturbed, humans can quickly take strategies to restore faulty products with limited resources.

[0046] S4 divides the product structure into normal structure and failure-prone structure based on the constructed disturbance-structure-function failure network and failure-prone functions; and updates the failure-prone structure based on the update function mapping.

[0047] According to the disturbance-structure-function failure network, the structure (S) of the product can be divided into normal structure ( ) and failure-prone structures ( ). Remap the new functions to the structural domain to adjust the failure-prone structure. The new functions constitute an updated function set The improved structure also constitutes a set of structures that are prone to failure and update ,The mapping relationship between the two sets is expressed by the design matrix [DM], as shown in the following equations (7)-(9).

[0048] (7); 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.

[0049] (8); (9); In the formula, [ DM ] represents the design matrix; represents the updated structure set of vulnerable structures; 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.

[0050] For example, for the grab bucket of the drilling equipment (corresponding to the excavation function), the design matrix between the update function and the update structure is: .

[0051] In this embodiment, for the hole-forming equipment design, toughness design factors are configured for the functions that are prone to failure, and the new functions formed after the function adjustment are further mapped back to the structural domain, and the structures that are prone to failure are adjusted, and finally a new structure after improvement is obtained, such as Figure 8 shown.

[0052] S5 combines the normal structure with the updated structure to obtain several tough product design solutions.

[0053] The tough product design solution is expressed as: (10); In the formula, Represents a resilient product design.

[0054] In this embodiment, in the design of hole-forming equipment, for the same kind of functional 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 tough product design solution for use in subsequent solution configuration.

[0055] 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.

[0056] The obtained structure sets are combined and configured into different toughness design schemes. In the process of configuration, it is necessary to consider whether the cost, environment, and product attributes are affected. In the present invention, cost, weight, and carbon emissions are introduced as constraints for configuring toughness design schemes, representing the requirements for product budget, lightweight, and environmental factors. The NSGA-Ⅱ algorithm is used for solving and a compromise solution for minimizing product carbon emissions, cost, and weight is obtained.

[0057] Here we mainly consider the cost, carbon emissions and weight of the updated structure, and the objective function is: (11); 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 Functionl 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 a structure (i.e. post-processing); 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: (12); In the formula, , , They represent the maximum values ​​of cost, carbon emission and weight respectively; Represents additional cost factors, such as operations, supply chain management, environment, etc. that are not taken into account.

[0058] Cost considerations mainly include expenses related to purchasing raw materials, design, manufacturing, and services. Weight refers to the cumulative weight of the structure after all parts are assembled. Carbon emissions mainly measure the carbon footprint of the entire life cycle of the product, 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 item in the above formula (12)). Finally, after the non-dominated sorting and congestion calculation of the NSGA-Ⅱ algorithm, the Pareto solution set of candidate resilient design schemes is obtained.

[0059] In this embodiment, the cost, carbon emissions, and weight of the updated structure are calculated respectively, as shown in Table 2. The mathematical model established according to formulas (11)-(12) is used and the NSGA-Ⅱ optimization algorithm is used for calculation. Finally, the candidate toughness design scheme is obtained, as shown in Table 2. Fig. 9 shown.

[0060] Table 2 Updated structure of drilling equipment

[0061] Compared with other alternatives, Scheme 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3) stands out from other solutions with its lower cost and weight, and performs its functions to meet user needs while enhancing product toughness. For all functional failures, Scheme 1 performs predictive maintenance, which can predict structural failures in advance and take corresponding measures to minimize the economic burden on users. For the failure of the excavation function, the three-axis inclination and tension sensors detect the breakage of the grab arm, and the control center drives the motor to retract the broken grab arm, and the remaining three grab arms continue to complete the work. For the failure of the traction function, under the same cyclic load, multi-rope linkage is used instead of single wire rope to reduce wear. The tension sensor is used to detect whether the wire rope is broken, and the tension abnormality is discovered in time by learning the tension data, and the learning module is used to predict the time when the wire rope may break. For the damage of the support function, the reinforcement ribs are used to enhance the ability of the mast to resist the cyclic overturning moment, and the strain gauges are used to monitor whether the mast is broken. For the failure of the crawler walking function, displacement, vibration sensors and learning modules 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 the failure of the fixing function, Nord-lock bolts are used to absorb the cyclic load to prevent the arm bolts from loosening, and the damaged arm bolts are replaced manually. In summary, Solution 1 can improve the toughness of the product while meeting user needs within an acceptable cost, carbon emissions and weight range, such as Fig. 9 shown.

[0062] Those skilled in the art will appreciate that the embodiments herein are intended to help readers understand the principles of the present invention, and should be understood that the protection scope of the present invention is not limited to such specific statements and embodiments. Those skilled in the art can make various other specific variations and combinations that do not deviate from the essence of the present invention based on the technical revelations disclosed by the present invention, and these variations 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 functions 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 functions of cost, carbon emission and weight in the design of resilient products are: ； 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.

Images