The degradation analysis of products has been demonstrated as a significant toolkit for reliability analysis.Datafrom the same batch of products in different working environments cannot be directly used to analyze product reliability. In this paper, motivated by this circumstance, we first assume that degradation data sets from different working environments are subject to different inverse Gaussian process models, and maximum likelihood estimation is used to obtain multiple model parameters. Secondly, we construct evidence by quantifying different information ofproducts, apply the evidence theory to fuse model parameters, and then analyze the reliability of products from the same batch. Finally, we use performance degradation data of the laser to illustrate the method.

Ring die pellet millsare widely applied in feed and biomass fuel. Particles are formed by rotating ring die, so torsional vibration is essential. Because the material has randomness in the extrusion process, the torsional vibration of ring die pellet mills is random, which affects the life, stability, and reliability. Using Lagrange equations and the lump-mass method, the torsional dynamic model of the ring die pellet mill is established. Based on the stochastic volatility model, the extrusion force is created. The dynamic equation of the ring die pellet mill is solved using the Runge-Kutta integration method, and the results show that the torsional vibration is related to the extrusion force, rotational speed, errors in installation, and fabrication. The torsional vibration and the torque of the ring die have similar changes in trend. The error affects the torsional vibration when it reaches a certain level.

Considering the complex multi-dimensional relationship of equipment in the equipment system, this paper constructs a spatialstructure network that reflects the spatialrelationship between equipment and a functional structure network that reflects the command and controland collaborationof equipment. Based on this, a bi-layer coupled complex network model is put forward. Combined with the relevant characteristics of equipment architecture, the structural characteristics of each network and evaluation parameters of the node importance are determined, and coupled intensity is confirmed by the improved group analytic hierarchy process.The evaluation method of equipment node importance is determined. Finally, the rationality and effectuality of this method arevalidated throughthe example analysis ofa synthetic battalion executing offensive operation tasks.

During spacecraft missionsin some countries all over the world, a number of failures have been observed that were due to the lower reliability of thermal protection of launch vehicles, so the reliability of base heating prediction and thermal protection is very important for successful emissions. The thermal protection of launch vehicles is usually carried out according to the base heating prediction. The base heating environment is a complicated combination of exhaust plume radiation, reversed plume flow convective heating, and engine nozzle radiation. In this paper, the numerical analysis of baseheating is performed to improve the precision of the predictive analysis,and then the flow is modeled using a two-dimensional, Reynolds averaged, and compressible Naive-Stokes equations and DSMC for a chemically frozen mixture gas. After that, the radiation is modeled by using RMC. On the basis of this elaborate base heating prediction, the weaknesses of the thermal protection can be found and the elaborate thermal protection can be realized, so the reliability of base heating prediction and thermal protection methodology can be increased.

In order to improve the reliability and economic benefit of fan operation, a state estimation and residual life prediction method of fan spindle bearing based on grey Markov chain is proposed. Firstly, a grey distribution model of bearing wear conditionofthe wind turbine main shaft is established. Then, using the residual error correction (Markov prediction analysis method) and division of bearing wear state grade, which determines the state level interval limits, the main shaft bearing wear state transition probability is calculated and the state transition matrix of the Markov process is constructed. Finally, this method is used to calculate the life of the main shaft bearing of the wind turbine.

The D-knotter is the core institution of the small baling machine, and it is affected by the quality of the machine, the working environment, the use and maintenance, and other factors. The knotter in the actual baling operation often fails to achieve the premature failure of the service life, reduces the harvesting efficiency of forage grass and straw, and increases maintenance costs. Therefore, by analyzing the failure modes and failure mechanism of the knotter, the root cause of the knotter failure is determined to be the wear of five different-sided shaft holes on the frame body. By installing bronze bearings lubricated with lithium grease on the shaft holes of the frame body, the wear of the shaft hole can be greatly reduced, thereby greatly improving the reliability of the knotter.

In order to realize the vertical and horizontal arrangement of square bales, the tie arm device adopts position feedback and hydraulic two-way lock loop for position control and position locking. The corresponding simulation model is established with AMESim software to verify the correctness of the model and to study the characteristics of the hydraulic control system. The fuzzy Failure Mode Effects and Criticality Analysis (FMECA) method is applied to the hydraulic system. According to the results of the hazard degree evaluation, the order of the hazard grade of each failure mode of the hydraulic system components is obtained and can be used for the reliability improvement and maintenance of the hydraulic system. The hydraulic control system is optimized by adjusting the parameters of several important influencing factors.

Wind turbines work in harsh environments and have changeable loads. The reliability and service life of the wind turbine gearbox has become an important factor for maintaining its safe, stable, and reliable economic operation. The production practice shows that the failure of the wind turbine gearbox is closely related to the structure and performance of the lubrication system. In this paper, the fault tree of the wind turbine gearbox lubrication system is established. It is pointed out that the temperature, state, and lubrication intensity of the lubricating oil are not well adapted to the working condition of the gear box, which leads to frequent gearbox breakdowns until its failure. The heat dissipation power consumption of the lubrication system is determined by calculating the heat balance of the lubrication system. By introducing the AI control method, the adaptive lubrication system framework of the wind turbine gear box is constructed from the aspects of oil temperature, oil pressure, oil level, and oil quality, which can automatically adjust the lubrication intensity according to the working condition of the wind turbine, so as to improve the lubrication effect of the wind turbine gear box. The research work in this paper plays an important role in optimizing the performance of the lubrication system, reducing the failure of the lubrication system, and reducing the operation and maintenance cost of wind turbines.

Slight vibrationsin the reciprocating brush cutter blade reciprocating motion will seriously affect crop quality problems. A method of application of topology optimization theory for the stubble cutter method was put forward in this paper. Firstly, the finite element software ABQUS was used to simulate the stubble of Salix psammophila,and the stress of the blade during the stubble was obtained according to the stubble blade during the stress conditions of topology optimization. According to the comparison of the simulation cutting conditions before and after double-action cutting, the stress is more uniform after optimization, the maximum force is reduced, and the stubble effect is obviously improved. Through theoretical analysis and cutting test analysis of tool life after topology optimization, it was found that the topology optimized double-action knife is improved and has a longer life expectancy. This study provides the basis for the development of reciprocating shrub stubble blades.

In view of the complex fault diagnosis theory of complex equipment electromechanical systems and the difficulty of all maintenance process maintenance personnel, the ontology was introduced as a technical tool for knowledge modeling. Based on the analysis of fault diagnosis, maintenance process of knowledge structure and electromechanical systems, anduse of protégé,the fault diagnosis and maintenance process of knowledge models of electromechanical systems was constructed. The faults diagnosis and auxiliary generation of the maintenance process for electromechanical systems were realized through FaCT++ reasoner to infer the constructed ontology. The model was verified, and the fault diagnosis and maintenance process knowledge could be integrated. Sharing and improving the efficiency of knowledge organization and maintenance technical support provide new technical means for effectively managing knowledge in the field of using electromechanical systems.

In view of the spare parts supply route problem with hard time windows in transportation, an optimal model that aims to minimize the total delivery time is put forward. In this paper, the supply route optimization problem with the shortest transportation distance as the decision target is discussed in detail. Taking the shortest total transportation distance of all vehicles as the optimization goal, a mathematical analytical model thatc onsiders the hard time window requirements of each customer is established. Based on the improved ant colony algorithm, the algorithm flow of solving the vehicle routing problem with hard time windows is designed to solve the difficulty of the model. In addition, the feasibility of the improved algorithm is verified by a case considering the actual terrain. The results show that the improved algorithm can quickly find the solution of VRPTW and provide an effective delivery plan for decision makers.

In order to make a vacuum pouring cylinder cover have an improved function, where two large solid rocket engines rather than one can be poured through simultaneously in a vacuum environment, the structure of the original vacuum pouring cylinder cover should be reformed. In addition to the original one, two other pouring ports are required. Therefore, to ensure its strength and stiffness properties, some stiffeners (or stiffen ribs) should be welded on its inner surface. Based on the response surface method and finite element analysis method, a multi-objective optimization model is obtained to optimize the structure of the two-engine pouring cylinder cover. Three sizes related to the stiffeners are defined as design variables, and the structural stresses and deformation values are calculated by using ANSYS software. Box-Behnken design experiments are conducted after narrowing the range of design variables by using a combination test. Design-Expert,a kind of common experiment design software, is used to optimize and solve the response surface. The optimal values of sizes of stiffeners for the two-engine pouring cylinder cover structure are obtained. The research results build asolidfoundation for the practical application of the project.

Operational readiness is one of the most important indexes of operational capability and the overall index for the effectiveness of the equipment support system of system (SoS). A scientific and reasonable assessment model is of great significance for optimizing the structure of the support SoS and improving the effectiveness of the support SoS. Aiming at the problem of inadequate consideration of the support factors in the existing assessment model, a new assessment model of the operational readiness rate that considers a variety of support factors is proposed. From the perspective of equipment support mission requirements, the equipment readiness assessment models for a single combat unit and multiple combat units are constructed. Finally, the accuracy of the proposed model is verified by an example analysis and comparison, and the influence of different support factors on the operational readiness rate is quantitatively analyzed.

The metal magnetic memory (MMM) technique can be effective in determining the initial damage of materials and structures in service and is partly applied in engineering. However, the real signals measured in engineering practice usually contain interference of the background magnetic field and measurement noise. For the influence of the background magnetic field, we designed a measuring probe constituted by two magnetic sensors that were arranged at different heights in the same vertical direction. Through the channel compensated method, we extracted principal features of the self-magnetic leakage field (SMLF) signal. As for the influence of measurement noise, we built the structure elements combined with the SMLF signal characteristic and investigated multi-scale morphological filtering to reduce the noise. The simulation and experiment results show that the proposed methods can not only suppress the background magnetic field and many kinds of noise but also protect the SMLF signal detail effectively.

The optimization design problem of customized passenger car cockpits layout is increasingly complexand of growing interest in the Chinesecar market.A new system is proposed to solve this problem based on ergonomic principles.Firstly,based on Kendall’s W, groups and optimization sequences of facilities are determinedusing a combination of Delphi and the analytic hierarchy process. Secondly, the degree of crowdedness in the cockpit layout can be controlled by users’ preference. Thirdly, a particle swarm optimization (PSO) algorithm is adapted to three-dimensional car cockpit layout optimization, and the resulting inertia-adaptive PSO is compared with some typical algorithms to show superiority. Finally,the results are reasonablyanalyzed in ergonomic simulation software. Thus, the proposed platform is demonstrated to be feasible and effective.

Regarding the industrial heritage of Changchun as creative tourism resources, this paper explores the possibility of integration between creative tourism and industrial heritage protection from the perspective of tourism. Based on the status investigation, this paper summarizes the characteristics of Changchun’s industrial heritage and conducts a SWOT analysis, and then puts forward the development strategy, mode, and overall planning intention on creative tourism of Changchun's industrial heritage.

Creative computing is very popular in recent years and has great potential. The introduction of systematic creative mechanisms and principles can provide solutions to practical problems, such as potential forgery and tampering of trade data in traditional supply chains. Guided by being creative, this paper proposes a new trusted data management scheme based on blockchain. First, a smart contract suitable for supply chain is designed to code trade rules in order to prevent performance risks and improve the credibility of trade data processing. Then, a ZSS04 scheme and sampling techniques are used to complete transaction data integrity check.Furthermore, an optimized PBFT consensus mechanism is proposed to achieve efficient, low cost, and scalable transaction data management. Finally, the trusted data management in untrusted environment is implementedby using the native characteristics of blockchain. Results show that the scheme can provide new ideas and technical support for transaction data management in supply chain.

The study of human creativity has never been stopped. Nowadays, although various kinds of computing technologies, such as online courses, research tools, virtualising applications, and professional applications, have been widely used to serve human creativity, the contradiction between the subjectivity of human creativity and the objectivity of computing technologies still cannot be reconciled very well. As the relationships between human creativity and computing technologies are being pushed forward, more possibilities have been explored, such as digital creativity and computational creativity. Within digital creativity, artists can have deeper cooperation with technologists. Some artists even could work with technology by themselves. By creating from the perspective of technology, more creative ideas may be discovered. Computational creativity is devoted to facilitating human creativity by imitating human creativity. Based on the great computing power, it aims to generate new ideas that we humans may not be able to come up with. However, due to the deep utilisation in creativity fields, computing technologies have been influenced dramatically by the elements of creativity. People have started to consider what else computing technologies could do for human creativity. Therefore, the concept of creative computing that requires computing itself to be creative has been proposed to serve human creativity better. Within this paper, various synergy possibilities between human creativity and computing technologies are discussed thoroughly for the improvement of human creativity.

A World Heritage Site must be of outstanding universal value and meet at least one out of ten selection criteria that in some respect as a geographically and historically identifiable place having special cultural or physical significance. Therefore, an increasing number of World Heritage Sites have been developed to be the tourist attractions worldwide. Tourism resources of the World Cultural Heritage Sites are used for protecting the heritage and providing better service for the tourists. Therefore, achieving a reasonable and effective resource allocation and resource supervising system is required. This research aims at solving such problem. The artificial intelligence techniques, especially the neural network algorithm is used in this research to complete massive calculations, including facing detecting and recognising, resource elements parameters calculation, and so forth. Creative computing theories and methods are working for combining the tourism area with computer science area. To express the system more explicitly, a case about Hailongtun World Cultural Heritage Site, which located in the Guizhou province in China, is used for testing the system.

Internet of things aims to create valuable results by responding to changing environments intelligently and creatively. Expected properties of Internet of things include autonomous, cooperative, situational, evolvable, emergent, and trustworthy, which are also required by any business operators. An approach is generated in this research to extract data relations from a multitude of business information through the design of a Game Theory Data Relations Generator (GTDRG) framework that extracts data relations by deducing the relationship among factors in game theory models. GTDRG relies on both creative computing and Internet of things combined base in order to generate outputs including, but not limited to, relation graph or game theory model mapping through GTDRG. When the proposed framework is established, it is crucial to interpret business information according to user requirements and make Internet of things components react to a changing environment. In summary, users’ needs and requirements can be satisfied by software through the help of the designed model, so that not only can existing data relation be extracted, but also the software can be built to make predictions based on data relations; and more importantly, it can save costs for organisations in addition to improving the effectiveness and efficiency of businesses in a creative way.

This paper analyses the development trends of intelligent instrument interfaces by applying full liquid crystal display technology. A novel reference dimension is introduced to consider related design work. In the perspective of design issues: how can we accurately analyse the requirements of drivers with various proficiency for different information, and how can instrument interfaces intelligently adapt to all kinds of drivers? This paper summarises the key points of the design work based on changing interface analysis in new automobile instruments and provides an analytical approach to targeting driving information: the index weight analysis method. A set of scientific methods to judge the degree of information requirements from various drivers in different scenarios is proposed. Therefore, it can improve the current situation that designers mainly rely on personal experience and subjective judgment when they design automobile instrument interfaces, which lacks scientific and objective judgment basis.

With the advent of the big data era, the response speed of traditional legacy systems is gradually unable to meet the requirements of users. Because legacy systems carry domain knowledge and critical resources, many organizations are migrating legacy systems to cloud platform so as to maximize the reuse of legacy systems as well as improve the performance of big data processing. MapReduce is recognized as an effective programming model for processing big data in parallel mode in cloud computing. Therefore, how to creatively combine parallelizable legacy code and the MapReduce model to enable legacy code to be accurately mapped into the MapReduce model is a challenging issue. We use the first type of creative computing to propose an approach for legacy code refactoring. The legacy code of big data processing is divided into several types according to the business logic, and then the corresponding refactoring rules are proposed. We use the second type of creative computing to develop a tool to support the refactoring process. The experimental results indicate that the refactoring results are correct and efficient in practical scenarios.

Smart jewelry is a subcategory of wearable devices. Compared with conventional jewelry, smart jewelry has advantages such as beautified appearance, wearability, and practicability. As an emerging category, smart jewelry has attracted much attention from developers and consumers, but it is still at an initial stage of development and is faced with arduous difficulties and challenges. This paper analyzes the consumption characteristics and market performance of smart jewelry products and focuses on the innovation strategies of smart jewelry products in the future. How can developers diversify the functions of jewelry with wearable computing technology and actively seek for difference and change under existing conditions? The innovation of smart jewelry products shall center on the users and the new thought of future development shall be explored starting from cross thinking, scene innovation, and blur boundary so as to find out the new relationship between smart jewelry and humans and provide the reference for developers. With the development of science and technology in the future, miniaturization and diversity will make the boundary between smart jewelry and conventional jewelry increasingly indistinct, and wearable computing will enrich the interaction mode between humans and jewelry. The developers shall have moreopen attitudes and take “innovation” as the core driving force of product development so as to reconstruct the aesthetics and connotation of jewelry and bring more possibilities for jewelry.

Livelihood oriented urban planning management (LOUPM), which holds that all economic and political activities center on human development, involves many aspects like the object, subject, system, and its aim. This paper aims to address the optimisation of LOUPM aspects through creative computing. Software systems will be engineered to help achieve optimised solutions in urban planning and management. By involving artificial intelligence, the proposed controller is engineered to output related data,which will be re-inputs of edited results into the system. This paperraises a way to improve the context-aware ability ofthe controller through a data manipulation toolthat enhances the self-adaptive software to solve both certain and uncertain problems especially in livelihood oriented planning and management. The controller employs control theory-based modules and combination-based modules to generate outputs more than activities with costs or balanced scorecards. In this process, Livelihood Orientation (LO) context sensors are added. The controller with LO sensors relies heavily on the extraction and filtering of LO data collected and should be capable of reacting to environment changes. Thus, this controller enables the self-adaptive software to know users’ needs precisely. Not only can the preset parameters be changed, but also the self-adaptivity is able to modify parameters. This creative approach is economical, effective, and efficient in LOUPM.

The activation of intangible cultural heritage has received much attention in recent years. Especially in tourism, there have been different activation forms for intangible cultural heritage, such as museum display, time-honoured brand, festivals, interaction activities, tourism products, and so on. Compared with other forms, the design of tourism products is more preferable, as the core idea of the activation is to associate the traditional culture with the modern time. However, the inheritors have various kinds of limitations (e.g., lack of education) to meet the requirements nowadays. It is particularly difficult for inheritors to achieve some kind of innovation for the activation of intangible cultural heritage. Various kinds of computing technologies have been widely utilised in different fields. Even artistic fields benefit greatly from them. In the meantime, due to the deep utilisation, the creative elements within artistic fields also influence the computing dramatically, which generates a variety of new concepts in the computing field. Creative computing, which is one of them, aims to improve human creativity by computing through creative ways. Therefore, in this paper, the study focuses on trying to apply the ideas of creative computing to facilitate the innovation of inheritors for the activation of intangible cultural heritage.

Understanding the contents of smart tourism comprehensively can provide abundant guidance and reference for the practices of smart tourism. It also helps to identify and overcome the shortcomings of smart tourism research. Based on the core ideas of creative computing, this paper constructs a word frequency matrix and performs cluster analysis by using keywords from smart tourism research. Then, the relevant keywords are extracted by using chi-squared statistics to interpret the cluster results. The results show that many creative articles focus on tourism information, the status quo and countermeasures of smart tourism, tourism information technology, and smart tourism scenic area management, which are the hot topics of domestic smart tourism research. Furthermore, tourism big data, tourism service supply chain, Internet+ tourism, and tourism experience have recently attracted increasing attention. The impact of tourism industry policy and the application of new information technology have always been an important source of creativity in smart tourism research.

The extensive application of digital technology and the development of technology have brought new opportunities for traditional exhibition space design. In the past, particular places were displayed mostly through text, display board, video and device, etc. The traditional exhibition way has very important significance for cultural dissemination but has shortcomings in preparation space experience restoration. The application of new technology can help the exhibition space design present in a new way. The author defines this method as the semi-virtual exhibition space, and in the construction of this space, the virtual display medium is arranged according to the space position of reality. The content of space-time change and site behavior change is aided by the designed script. This kind of exhibition space construction has raised higher requests to the designer, regardless of the designer’s own knowledge structure, and adapts the new technology innovation. Both need to adapt to the challenges brought about by this development. This paper expounds this new concept and discusses how to construct a new knowledge system.

With the development of modern society, human beings are more and more aware of the importance of creativity. As a new area of research, creative computing will play a bigger role in life. There is no doubt that a large pool of knowledge is the foundation of creativity. Research shows that legacy systems contain not only a great deal of domain expertise but also many reusable components. From this point, a new component extraction approach is proposed to extract reusable components of the system and provide better foundation and inspiration for creativity. Experiments have shown that this approach can extract reusable components efficiently, which is helpful for creativity.

With the development of science and technology, the research and application of building-integratedphotovoltaic (BIPV) has become a hotspot.In this paper, we present acreative design scheme using an optimization algorithm called LOLP algorithm of a set of independent photovoltaic (PV) systems in remote areas of Jilin Province. Through the aiding design of the professional photovoltaic system PVsyst software, we discuss the improvements after using this creative design method in the software.

Assuming creativity is not the same as intelligence and we know that intelligence can be generated by computing (AI), can we generate creativity with computing and call it Artificial Creativity (AC)? What is the connection between AI and AC? This article is attempting to answer these questions and to is propose a system to generate creativity. Human intelligence has been researched for years by psychologists and biologists. Then, based on working mechanism of human brain, computer scientists developed neural network algorithm and other machine learning algorithms to generate intelligence. Creativity is a unique characteristic of living creatures. Recently more work has been on generating creativity through combining creativity theories and artificial intelligence algorithms.

A nonlinear finite element analysis (FEA) on rectangular concrete-infilled tubular (CFT) column connections was conducted using the FEA software ABAQUS. In this analysis, loading path and stress distribution of the anchored blind-bolted (ABB) connections to CFT columns were clearly defined; influences of strength grade of bolts, thickness of endplates, vertical interval between bolts, diameter of bolts, and pretension on bolts on the studied connections were determined. The results of FEA indicate that the flush endplate connections of ABB CFT columns are typical semi-rigid connections. The established finite element (FE) model was verified by test results of six anchored blind-bolted flush endplate connections to CFT columns. The test results show that the model can accurately simulate mechanical performance of the ABB connections and is suitable for different forms of ABB connections to CFT columns.

The target detection and tracking technology of the unmanned aerial vehicle (UAV) is an important research direction in the field of UAV aerial photography. In order to effectively and accurately detect vehicles in a UAV platform and in complicated road environments, the authors proposed a vehicle detection method based on saliency region detection. First, the saliency map of the target is calculated by using the salient region detection method based on the optimized frequency-turned. Next, segmentation methods based on Boolean Map and OTSU are combined to determine the region of interest of the vehicle target in the saliency map image. Finally, a series of vehicle apparent features-based methods based on geometry, symmetry, and horizontal edge wave are used to determine the vehicle and eliminate the interference of roadside objects accurately. Experimental tests carried out from different datasets show excellent performance in multi-vehicle detection in terms of accuracy in complex traffic situations and under different scales and angles of aerial images, realizing fast vehicle detection on the UAV platform.

In order to solve the shortcomings of the smart campus message system constructed by the current method in network indicators, data processing, business interface, human-computer interaction,and other technologies, a cloud computing algorithm-based smart campus message system construction methodwas proposed. In this method, the LAN interconnection, the network multimedia terminal, and the network architecture platform were established by the cloud computing algorithm. This method established the awareness of smart campus development, established the cloud smart campus management norm system, and constrained the network environment based on the cloud smart campus. The overall structure of the smart campus message system was constructed from the technical level, the main layer,and the constraint layer. The functional module analysis of the smart campus message system software was performed, which had two major categories, including basic function modules and extended function modules. It achieved the construction of a smart campus messaging system based on cloud computing algorithms. The experimental results showed that the proposed method had obvious advantages in network indicators, data processing, business interface, human-computer interaction and other technologies which can bring a lot of convenience to the school staff.

The detection of similar duplicate records was a key link in database data cleaning. In the process of detecting duplicate records in the same amount of data, the record attribute dimension was too high, which led to the problems of precision, recall and time efficiency. A database repeat recording detection method based on the IQPSO (Improved Quantum Particle Swarm Optimization) algorithm was proposed. The method constructed an entropy metric in terms of the similarity between objects, and evaluated the importance of each attribute in the original data set of the database, thereby removing unimportant or noise attributes. A subset of key attributes was preferred and attribute dimensions were reduced.Large data sets were divided, in the database, into multiple disjoint small data sets based on key attributes. Each small data set was used as an input to the support vector machine. The IQPSO algorithm was used to optimize the parameters of the support vector machine to obtain the optimal parameters of the support vector machine. The repeated record detection model was constructed according to the optimal parameter training classifier, and the model was used to perform similar repeated record detection. The experimental results indicated that the proposed method effectively improved the detection efficiency under the premise of ensuring the highest recall rate and precision. The proposed method also solved the problem of database similar duplicate record detection effectively.