Search Results (20)

The K-means algorithm utilizes the Euclidean distance metric to quantify the similarity between data points and clusters, with the fundamental objective of assessing the relationship between points. It is important to note that, during the process of clustering, the relationships between the remaining points in the cluster and the points to be measured are ignored. In consideration of the aforementioned issues, this paper proposes the utilization of extension distance for the purpose of evaluating the relationship between the points to be measured and the cluster classes. Furthermore, it introduces a variant of the K-means algorithm based on the separator distance. Through a series of comparative experiments, the effectiveness of the proposed algorithm for clustering fan-shaped datasets is preliminarily verified. Full article

In the context of Industry 4.0, user demands for industrial robots have shifted toward diversification and experience-orientation. Effectively integrating users’ affective imagery requirements into industrial-robot form design remains a critical challenge. Traditional methods rely heavily on designers’ subjective judgments and lack objective data on user cognition. To address these limitations, this study develops a comprehensive methodology grounded in Kansei engineering that combines Extenics-based semantic analysis, eye-tracking experiments, and user imagery evaluation. First, we used web crawlers to harvest user-generated descriptors for industrial floor-cleaning robots and applied Extenics theory to quantify and filter key perceptual imagery features. Second, eye-tracking experiments captured users’ visual-attention patterns during robot observation, allowing us to identify pivotal design elements and assemble a sample repository. Finally, the semantic differential method collected users’ evaluations of these design elements, and correlation analysis mapped emotional needs onto stylistic features. Our findings reveal strong positive correlations between four core imagery preferences—“dignified,” “technological,” “agile,” and “minimalist”—and their corresponding styling elements. By integrating qualitative semantic data with quantitative eye-tracking metrics, this research provides a scientific foundation and novel insights for emotion-driven design in industrial floor-cleaning robots. Full article

The widespread scrapping of retired mechanical parts has led to severe waste of resources and environmental burdens, posing a significant challenge to sustainable industrial development. To enable efficient recycling of retired mechanical parts and enhance the sustainability of their remanufacturing processes, the concept of biological genes is adopted to characterize the changes in the information of retired mechanical parts during the remanufacturing process as gene mutations of parts, aiming to maximize remanufacturing potential and devise an optimal generalized remanufacturing strategy for extending part life cycles. However, gene mutation of retired mechanical parts is not an isolated event. The modification of local genes may disrupt the original equilibrium of the part’s state, leading to conflicts such as material–performance, structure–function/performance, and function–performance. These conflicts constitute a major challenge and bottleneck in designing generalized remanufacturing schemes. Therefore, we propose a conflict identification and resolution method for gene mutation of retired mechanical parts. First, gene mutation graph of retired mechanical parts is established to express its all-potential remanufacturing pathways. Using discrimination rules and the element representation method from extenics, mutation conflicts are identified, and a conflict problem model is constructed. Then, the theory of inventive problem solving (TRIZ) engineering parameters are reconstructed and mapped to the mutation conflict parameters. The semantic mapping between the inventive principles and the transforming bridges is established by the Word2Vec algorithm, thereby improving the transforming bridge method to generate conflict resolution solutions. A coexistence degree function of transforming bridges is proposed to verify the feasibility of the resolution solutions. Finally, taking the generalized remanufacturing of a retired gear shaft as an example, we analyze and discuss the process and outcome of resolving gene mutation conflicts, thereby verifying the feasibility and effectiveness of the proposed concepts and methodology. Full article

Fresh produce, as a primary source of nutrition, plays a pivotal role in daily life. However, the unique characteristics of fresh produce—such as perishability, widespread production, short shelf life, long distribution cycles, and high volatility in both supply and demand—render the fresh produce supply chain particularly vulnerable to disruptions. These vulnerabilities not only impact daily consumption but also pose significant challenges to the operational efficiency of enterprises. Enhancing the fresh produce supply chain resilience is crucial for businesses to effectively mitigate risks, ensure consistent product quality, and maintain overall supply chain stability. Nevertheless, there remains a lack of clear, process-oriented guidance for developing resilience improvement strategies within the fresh agricultural product sector. Specifically, there is insufficient clarity regarding which elements should be prioritized for investment in resilience strategies, how these strategies should be formulated, and the absence of a theoretically sound framework to guide the strategic development of supply chain resilience improvements. To address the lack of scientific, quantitative, efficient, and specific processes for generating supply chain resilience improvement strategies in fresh agricultural product enterprises, this study adopts the framework of extensible primitive theory. Initially, an evaluation index system for the fresh produce supply chain is constructed, and the extendable evaluation method is employed to assess the resilience level of fresh agricultural product enterprises. This approach facilitates the identification of the key challenges that must be addressed to enhance supply chain resilience and helps generate strategies that reconcile previously incompatible issues. Next, the core objectives and conditions underlying the resilience incompatibilities in fresh agricultural product enterprises are quantitatively analyzed. Finally, the expansion transformation of both target and condition primitives is carried out to derive the optimal strategy for improving supply chain resilience. The study uses company M as a case example, where the evaluation results indicate that the company’s supply chain resilience is rated as “good”. However, several issues were identified, including inefficiencies in product supply, limited financing capacity, low enterprise visibility, and inadequate production and processing equipment. Based on these findings, the paper proposes a series of optimization strategies aimed at improving the fresh produce supply chain resilience through extension transformation. Full article

To solve the problems of chaotic information management and difficult traceability in the manufacturing process of transformer coils, a traceability and management method oriented towards the manufacturing process of transformer coils has been proposed. This method integrates industrial internet identification resolution and extension of Petri net modeling theory. A comprehensive identification and resolution framework for coil manufacturing processes has been constructed. In this manuscript, the authors proposed an industrial data-sharing space based on the producer-consumer model with unified coding identification. This enables information sharing for all resources, including personnel, machinery, materials, methods, environment, and measurements. A method for modeling extensible identification primitives of coil manufacturing process information was proposed, which formalizes the correlation and data structure of process information. A Petri net model for the comprehensive acquisition and integration of elemental information in coil manufacturing processes, as well as a mathematical model for quality traceability, were constructed, thereby forming a complete path for quality traceability information. Finally, based on the method proposed above, a software and hardware environment for identification and traceability for coil manufacturing was established. Taking a certain type of coil as an example, validation was carried out; the results indicate a significant enhancement in the production management and information traceability capabilities of the coil production workshop. This study provides reference and guidance for the process traceability management of power equipment manufacturing. Full article

The service performance of chromium-free zinc–aluminum coatings exhibits characteristics from multiple perspectives. Fully considering the physical properties, corrosion resistance, and economic viability of the coatings, this study incorporates the concepts of “domain” and “degree” from extenics theory into the analytic hierarchy process to optimize the formulation of chromium-free zinc–aluminum coatings. The findings reveal that the extension analytic hierarchy process takes into account the diversity of evaluation indicators, enhancing the objectivity and accuracy of the comprehensive evaluation results. Nine formulations were developed using a four-factor, three-level orthogonal experiment to evaluate the effects of metal powder, PEG-400, KH-560, and sodium molybdate on the service performance of chromium-free zinc–aluminum coatings. Utilizing an extensible hierarchical sorting weight system alongside a performance index grading and scoring method, 3# emerged with the highest score, indicating the best overall performance. The research outcomes offer innovative insights and technical support for optimizing the formulations of chromium-free zinc–aluminum coatings and other coatings. Full article

The main purpose of this paper is to develop an intelligent controller for the DC-link voltage of bidirectional soft-switching converters used in the batteries with equalizing charge and discharge control. To accelerate the equalizing charge and discharge speed of batteries, the DC-link voltage controller of the bidirectional converters is designed based on extension theory. Firstly, the photovoltaic module arrays (PVMAs) are used with the intelligent maximum power point tracker (MPPT) for supplying the power to the load side. Through the bidirectional soft-switching converters, the PVMAs will be allowed to carry out the uniform charging and discharging for the storage battery in order to achieve the intended energy storage and auxiliary power supply functions. In terms of the controller design, the quantitative design techniques are utilized, by which the P-I controller parameters will be designed for the converter when attempting to achieve the same control performance at different working points. As a next step, the aforesaid parameters are used together with the extenics theory. Based on the variation in the output power of the bidirectional converter and that in the voltage of the storage battery, it allows the system to find out the intended P-I controller parameters that will be approximate to the prescribed control performance when operating under different working conditions. As a result, the P-I controller will be provided with more efficient control flexibility and control performances. Finally, actual test results demonstrated that the response time of the proposed intelligent extension controller is shortened by 3% compared to the quantitative design of the proportional–integral (P-I) controller. Based on the proposed quantitative design of an intelligent controller for uniform charging and discharging management of batteries, the sustainable utilization of renewable sources of energy can be improved. At the same time, the better economic benefit of the energy preservation system is obtained. In addition, it also prolongs the life cycle of batteries, and then enhances the reliability of the batteries. Full article

A series of water diversion projects to address the uneven distribution of water resources in China have involved the construction of a large number of hydraulic tunnels. As the lining structure is there to maintain the stability and durability of the tunnels, durability damage can easily occur in the operation process, thus affecting the safety of water transmission and water supply capacity. Therefore, it is important to evaluate the durability of hydraulic tunnel lining structure. Considering the randomness and fuzziness of the factors affecting the durability of hydraulic tunnel lining structure, this paper proposes a comprehensive evaluation model based on the coupling of set pair analysis and extension. The G1 method and the simple correlation function method are used to determine the subjective and objective weights of the evaluation indexes, respectively, and the combination weight of them is assigned based on the principle of minimum entropy; next, the set pair analysis principle is used to establish the linkage affiliation function, which can calculate the comprehensive linkage affiliation of the object to be evaluated, and then the maximum affiliation principle is used to judge the durability level of the hydraulic tunnel lining structure. Finally, taking a section of hydraulic tunnel as an example, the model proposed in this paper is used to calculate its durability grade as Class III, with the set pair potential SHI(H) = 7.5856, which is consistent with the actual engineering practice, and a comparative study is done in combination with the AHP-Extenics method. It is verified that the evaluation model can scientifically and reasonably evaluate the durability of hydraulic tunnel lining structure, providing a basis for subsequent maintenance and reinforcement. Full article

Fujian Tulous in China are important international architectural heritage sites that reflect precious human cultural heritage. Currently, only a small number of Tulou buildings have been listed as world cultural heritage sites, resulting in a lack of attention and financial support for most Tulou buildings. Thus, it is difficult to effectively renovate and repair Tulou buildings to adapt to modern life, and therefore they are facing the severe challenge of abandonment and desolation. Due to the special conditions of Tulou buildings, there are significant limitations in renovation and repair work, with a number of problems such as the lack of innovative renovations. Therefore, through a problem model analysis of a design system for Tulou renovations, in this study, we adopt the methods of divergent tree, conjugate pair, correlative net, implied system, and split-merge chain analyses in extenics to carry out extension transformation and solve the problem and we verify its feasibility using the example of the Tulou renovation projects in Lantian Village, Longyan City. We explore an innovative methodology for scientific renovation of Tulou buildings, and we establish a design system for Tulou building renovations that enriches and supplements original renovation methods; thus, we provide a basis for the repair and reuse of Tulou buildings, to extend their service life and to realize the sustainable development of Tulou buildings. The research results show that extenics can be implemented in innovative renovations of Tulou buildings, and it is concluded that the essence of achieving sustainable renewal in Tulou building renovations is to solve contradictory problems, including contradictions in conditions, objectives, and design. This study verifies the possibility of applying extenics in the design of Tulou building renovations, makes corresponding contributions to the application of extension methods in the renovation and renewal of Tulou buildings, and also contributes to the renovation, renewal, and protection of other types of architectural heritage sites. Full article

(1) In recent years, with China’s increasing investment in the transportation industry, the construction of highways and bridges has flourished, bringing great convenience to people’s lives. At the same time, there are many uncertain factors in the process of bridge construction, being prone to construction risks. In order to meet the requirements of sustainable development, it is necessary to accurately evaluate the safety risk level of bridge construction. Therefore, it is necessary to establish a new scientific safety risk evaluation system for highway bridge construction. (2) Methods. Based on the relevant standards and specifications, this paper establishes a highway bridge construction safety risk evaluation index system, and then uses the cloud entropy weight method to objectively weight each risk index, using cloud model theory to conduct a risk assessment, and through the cloud model images directly determine the overall risk level of bridge construction, and the level of risk indicators. (3) Results. Applying this method to the construction safety risk assessment of a particular bridge, the overall construction risk level of the bridge is obtained as “level 4”, and the risk levels of the four first-level indicators are also all “level 4”. (4) Conclusions. The cloud entropy weight method proposed in this paper and the traditional AHP-Extenics method are applied to a bridge construction safety risk evaluation, and the evaluation results obtained are consistent. However, this paper uses the cloud model to improve the entropy weight method in order to calculate the weights, which fully reflects the objectivity of the assignment. The cloud model is used for evaluation, and the risk level of indicators can be determined visually with images. Full article

Extenics has unique advantages in solving contradictions by using formal models to explore the possibility of expanding things and the laws and methods of development and innovation. This paper studies the specific application of the extension strategy generation method in emergency cold chain logistics, in order to solve the problem that the emergency plan is difficult to cover in the face of an emergency. The purpose of this paper is to provide ideas for the generation of strategies to solve the contradictions of cold chain logistics in complex emergency scenarios. Giving full play to the unique advantages of extenics in solving contradictory problems, this paper analyzes the core problems, objectives and conditions of emergency cold chain logistics in four links with the case scenario of the COVID-19 pandemic outbreak, extends and generates 10 measures to form 36 schemes, and evaluates the combination schemes quantitatively and objectively using the dependent function and superiority evaluation formula. In addition, the consideration of carbon constraints is added to the selection of the scheme, and the specific plan of integrating e-commerce platform, expert guidance, establishing temporary cold storage transfer and contactless distribution is designed. The research results provide support for meeting the needs of emergency logistics schemes in different situations and optimizing the energy efficiency of the scheme while ensuring humanitarian support. At the same time, the application of extenics basic-element formal language also provides a reference for further applying artificial intelligence to the design of emergency logistics schemes. Full article

(1) In recent years, with the continuous increase of the state’s investment in infrastructure, the construction of highways and bridges has developed rapidly, which has brought great convenience to people’s lives. At the same time, with the increase of bridge service time, the reliability of bridges declines. In order to meet the requirements of sustainable development, it is necessary to accurately evaluate the reliability of bridges. However, most of the existing evaluation methods have single-weighting and one-sidedness. There are problems such as strong subjectivity and overly simple evaluation procedures. Therefore, it is urgent to establish a new scientific bridge reliability evaluation system. (2) Methods. In this paper, a bridge superstructure is taken as the research object, and the “Technical Condition Assessment Standard for Highway Bridges” (JTG/T H21-2011) is used as the criterion to establish a bridge reliability evaluation index system. The subjective and objective weights of the evaluation indicators are based on minimum discriminant information. Each evaluation indicator is combined and weighted; then, the closeness of each evaluation object to the positive ideal solution is determined according to Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS). Finally, the reliability level of each evaluation object is determined. (3) Results. Reliability evaluation of the three-span superstructure of the bridge was carried out, and final reliability evaluation results of “Grade 2, Grade 2, Grade 2” were obtained, which are consistent with the actual working state of the bridge. (4) Conclusions. The evaluation results of this paper are consistent with the results obtained by the traditional AHP–Extenics method, but the evaluation model of this paper adopts combined weighting, which avoids the one-sidedness of the weighting of a single method—thus, the comprehensive weight obtained not only reflects the subjective intention of decision makers, but also reflects the objective properties of the data. Full article

This paper presents a hybrid force/position control. We developed it for a hexapod walking robot that combines multiple bipedal robots to increase its load. The control method integrated Extenics theory with neutrosophic logic to obtain a two-stage decision-making algorithm. The first stage was an offline qualitative decision-applying Extenics theory, and the second was a real-time decision process using neutrosophic logic and DSmT theory. The two-stage algorithm separated the control phases into a kinematic control method that used a PID regulator and a dynamic control method developed with the help of sliding mode control (SMC). By integrating both control methods separated by a dynamic switching algorithm, we obtained a hybrid force/position control that took advantage of both kinematic and dynamic control properties to drive a mobile walking robot. The experimental and predicted results were in good agreement. They indicated that the proposed hybrid control is efficient in using the two-stage decision algorithm to drive the hexapod robot motors using kinematic and dynamic control methods. The experiment presents the robot’s foot positioning error while walking. The results show how the switching method alters the system precision during the pendulum phase compared to the weight support phase, which can better compensate for the robot’s dynamic parameters. The proposed switching algorithm directly influences the overall control precision, while we aimed to obtain a fast switch with a lower impact on the control parameters. The results show the error on all axes and break it down into walking stages to better understand the control behavior and precision. Full article

Low-carbon product design involves a redesign process that requires not only structural module modification, but more importantly, generating innovative principles to solve design contradictions. Such contradictions include when current design conditions cannot satisfy design requirements or there are antithetical design goals. On the other hand, configuration tasks in the reconfiguration process are interdependent, which requires a well-scheduled arrangement to reduce feedback information. This study proposes an effective configuration methodology for low-carbon design. Firstly, configuration tasks and configuration parameters are designated through quality characteristics, and the directed network along with the associated values of configuration tasks are transformed into the design structure matrix to construct the information flow diagram. Then, the Extenics-based problem-solving model is presented to address design contradictions: low-carbon incompatibility and antithetical problems are clarified and formulated with a basic-element model; extensible and conjugate analysis tools are used to identify problematic structures and provide feasible measures; the Gantt chart of measures execution based on the information flow diagram is constructed to reduce feedback and generate robust schemes with strategy models. The methodology is applied to the vacuum pump low-carbon design, the results show that it effectively solves contradictions with innovative design schemes, and comparative analysis verifies the performance of Extenics. Full article

Research on electroencephalography (EEG) signals and their data analysis have drawn much attention in recent years. Data mining techniques have been extensively applied as efficient solutions for non-invasive brain–computer interface (BCI) research. Previous research has indicated that human brains produce recognizable EEG signals associated with specific activities. This paper proposes an optimized data sampling model to identify the status of the human brain and further discover brain activity patterns. The sampling methods used in the proposed model include the segmented EEG graph using piecewise linear approximation (SEGPA) method, which incorporates optimized data sampling methods; and the EEG-based weighted network for EEG data analysis, which can be used for machinery control. The data sampling and segmentation techniques combine normal distribution approximation (NDA), Poisson distribution approximation (PDA), and related sampling methods. This research also proposes an efficient method for recognizing human thinking and brain signals with entropy-based frequent patterns (FPs). The obtained recognition system provides a foundation that could to be useful in machinery or robot control. The experimental results indicate that the NDA–PDA segments with less than 10% of the original data size can achieve 98% accuracy, as compared with original data sets. The FP method identifies more than 12 common patterns for EEG data analysis based on the optimized sampling methods. Full article