bluuebunny/crossref_metadata_2025_split huggingface dataset:
Study on Acoustic Radiation Calculation and Far Field Criterion of Oil pan
Authors: Huang Yue-zhen , Zhang Bo , Zhao Ke-lun , Xia Xue-bao 
Published: February 2021

Abstract
Diesel engine with low vibration and noise characteristics will be a major trend for the future development. As the shell part on the engine, the vibration and noise control of the oil pan is an urgent problem to be solved. It is of practical significance to predict the oil pan vibration and radiation noise during the design phase. An oil pan of diesel engine was taken as the research object, the finite element model of the oil pan was established and the finite element method (FEM) was used to calculate the oil pan vibration response. Three different numerical calculation methods (Finite element-boundary element hybrid method, finite element-infinite element hybrid method, finite element-automatic matching layer technology) were used to calculate radiated sound power level of the oil pan respectively. The calculation accuracy and efficiency of three different calculation methods were compared and analyzed. The results show that the finite element-boundary element method is more suitable for the calculation of the acoustic radiation of the oil pan. Finally, a method based on the directivity of acoustic radiation to determine the far-field acoustic radiation is proposed and verified.
Development of reliability testing device for grating encoder
Authors: Zhou Xin-Da , Chen Chuan-Hai , Tian Hai-Long , Yang Hai-Ji , Li Shi-Zheng 
Published: February 2021

Abstract
The technical index of a reliability testing device for grating encoder is determined based on the analysis of the working condition and fault cause of the grating encoder, and the overall scheme of the test device is designed. The support and mechanical structures of the operation fixture and loading device and the monitoring system of the test device are designed based on a modular design. The upper computer software is developed using LabVIEW, and the programming frame and the control interface are introduced. Reliability test is performed to verify the feasibility of the reliability testing device, and the degradation path of the predetermined degradation index is obtained.
Research on the Highly Accelerated Stress Screening (HASS) Test Process of Civil Aircraft Airborne Equipment
Authors: Lu Peng , Yang Xuerui 
Published: February 2021

Abstract
The reliability of the airborne equipment of civil aircraft is highly concerned by the aircraft Original Equipment Manufacture (OEM), airlines, passengers and airworthiness authorities, and is the key to ensuring the safety and punctual operation of the aircraft. The Highly Accelerated Stress Screening (HASS) test is one of the effective test methods to ensure that the product reaches the expected reliability level, and it has been widely used in aviation, high-speed rail, automobiles and other fields. Based on the characteristics of civil aircraft airborne equipment, combined with the universal method of HASS test, this paper investigates the application process of HASS test on airborne equipment, and gives the method for determining the test object of airborne equipment by HASS, and the test of HASS, the principles of test profile design, follow-up verification and troubleshooting methods. The research can be applied to the HASS test work of civil aircraft airborne equipment, and guide the development of HASS test, so as to effectively propose defective products in the manufacturing stage and improve the reliability of the installed airborne equipment.
Content Sharing Network based on IPFS and Blockchain
Authors: Xu Haimei , Cheng Yan , Li Zhengdong , You Chunyan 
Published: February 2021

Abstract
In this paper, we propose one content-sharing system InnerLight based on IPFS and BlockChain, which is a creation and public discussion platform about mental health. InnerLight put copies of articles from creators on IPFS to achieve distributed storage of contents and complete the first step of returning the data to creators. At the same time, it also encourages creators and readers to maintain the sustainable development of the system through blockchain-based cryptocurrency. In addition to IPFS and Blockchain, ranking algoithms contribute to make Innerlight to be a decentralized autonomous ecosystem.
Reliability Evaluation for Complex System Based on Bayesian Theory and Multi-Source Information Fusion
Authors: Song Zhaoli , Zhao Qian , Jia Xiang , Guo Bo 
Published: February 2021

Abstract
For large complex systems, it is of great importance to study effective approaches for reliability evaluation. In this paper, a system reliability evaluation method based on Bayesian theory and multi-source information fusion is proposed. Firstly, model the reliability of system network, including the establishment of system reliability block diagram and the determination of the system and components’ life distributions. Then, the posterior distributions and posterior moments of component reliability are determined. With the posterior moments, the failure information of components can be converted to the prior moment of the system reliability according to the system structure, and the system prior distribution can be obtained. Finally, combined with the system-level field data, the posterior distribution of system reliability can be obtained on the basis of Bayesian theory, and be utilized to evaluate the reliability of system. To fill out the shortage of field data, the proposed method in this paper can make full use of various quantitative and qualitative prior information with high accuracy.
An improved deep convolutional neural network with multiscale convolution kernels for fault diagnosis of rolling bearing
Authors: Fu Liangcheng , Zhang Li , Tao Junyong 
Published: February 2021

Abstract
With the help of multiple layers of nonlinear mapping capabilities, deep neural network models can adaptively extract fault features and diagnose faults, which improve the efficiency and accuracy of fault diagnosis. Based on Deep Convolutional Neural Networks with Wide First-layer Kernels (WDCNN), this paper proposes an improved model named Deep Convolutional Neural Networks with Multiscale First-layer Convolution Kernels (MDCNN). The proposed method uses 1D convolution kernels of different sizes to extract multiscale features from original vibration signals. Afterwards, to achieve feature fusion, different feature maps are reduced to the same size through adaptive convolution operations. Finally, through the learning of the multi-layer network, intelligent fault diagnosis from the signal to the health state is realized. A test based on CWRU dataset is performed to verify the accuracy of the proposed method for rolling bearing fault diagnosis. Results indicate that MDCNN shows higher performance than WDCNN.
Reliability analysis of discrete multi-state systems based on survival signature
Authors: Liang H , Mi J , Bai L , Cheng Y 
Published: February 2021

Abstract
System signature has been widely utilized to facilitate reliability assessment of coherent systems and networks consisting of a single type of components, which enables us to separate aspects of components’ failure time and system structure. Recently, survival signature fulfils the similar work, extended to the implementation of systems with multiple types of components. However, when the system has several states, the relevant work is limited to complete the reliability assessment by the survival signature. This paper proposed a novel pattern of survival signature for the multi-state system with multiple types of components and the presented approach is executed to demonstrate the validity via a numerical case with 2-type and 3-state components.
Structural dynamic reliability estimation with advanced extremum Kriging method
Authors: Zhao Y J , Lu C , Li H , Liu H T , Fei C W 
Published: February 2021

Abstract
To enhance the computational performance of the structural dynamic reliability estimation, advanced extremum Kriging method (AEKM) is proposed fusing Kriging surrogate model, multi-population genetic algorithm and response surface method-based extremum thought (ERSM) in this paper. The applicability of the AEKM is verified via the blisk radial deformation dynamic reliability analysis of an aeroengine high-pressure compressor. The results show that the reliability level of the blisk is 0.9956 as the allowable value of radial running deformation 1.75×10−3 m. Moreover, the developed AEKM is superior to other three surrogate models, including ERSM, K-ERSM and IK-ERSM, in terms of computing precision and analytical efficiency. Besides, the analytical precision of the developed method is basically consistent with the direct simulation, and the analytical time is obviously superior to the direct simulation. Therefore, the AEKM is illustrated to be an effective way for structural dynamic reliability analysis, which enriches complex structural reliability theory.
Instantaneous Availability of Multi-component System under the Constraint of Spare Parts
Authors: Wang Yun , Hu Pengwei , Jin Baidong , Cheng Hailong , Liu Yuhan 
Published: February 2021

Abstract
The availability of equipment is one of the most important indicators to measure support effectiveness of system, and spare parts supply is one of the key support resources, so it is necessary to consider the constraint of spare parts in the study of availability. As the evaluation of steady availability cannot meet the requirement of support effectiveness timely and accurately and the previous models of instantaneous availability are usually applicable to one-unit system. To solve the above problem, firstly, the whole process is divided into two sub-processes, i.e., the replace and repair process of fault system and the maintenance and turnover process of failure parts, then the influence between the two sub-processes is analysed. Secondly, a model that can compute the instantaneous availability of multi-component series system with spare parts is given. Finally, a numerical example is used to demonstrate the applicability and the performance of the proposed method.
Temperature characteristics of SOC estimation for traction battery system
Authors: Li D , Zhimao M , Mingsheng C 
Published: February 2021

Abstract
In order to determine the effect of temperature on the SOC estimation accuracy of the battery system, the electrical performance of the battery system was studied by charge/discharge and environmental testing equipment. When SOC is equal to or greater than 80%, the result shows larger error between the actual SOC of battery system and the recorded SOC of BMS system, which are 3.81% and 4.43% at -10 °C and 0 °C respectively, and the error is 2.41% at 25 C. The error between the actual SOC of battery system and the recorded SOC of BMS system tend to decrease firstly and then increase as the temperature increased, and the error is 0.31% at 25 C. In conclusion, temperature has a significant impact on the SOC estimation of battery system, the actual SOC of battery system shows a trend of rapid increase and followed by a rise slowly, while the recorded SOC of BMS system shows a trend of continuous increase, resulting in the error between the actual SOC and the recorded SOC. Besides, the minimum error of SOC estimation appears at 25 C.
Semi-supervised Fault Diagnosis Model Based on Improved Fuzzy C-means Clustering and Convolutional Neural Network
Authors: Wang Yumin , Han Minghong , Wu Yaman 
Published: February 2021

Abstract
The number of unlabeled data is much more than labeled data. There are some challenges in using existing complex data for fault diagnosis. Therefore, we proposed a semi-supervised fault diagnosis algorithm based on improved fuzzy C-means algorithm (IFCM) and Convolutional Neural Network (CNN). Firstly, the fault original signal is extracted by variational mode decomposition (VMD) and the singular value decomposition (SVD) to extract the fault feature vector. Secondly, IFCM is used to obtain the membership degree of the data to all categories, which integrates the labeled data into the cluster center of fuzzy C-means (FCM) to obtain better clustering results. The label of labeled data will spread to unlabeled data in the same category. Thirdly, data with a membership degree greater than the value of 0.9 will be selected as the core data set. Finally, the original signal and labels of core data set will be input into CNN for fault diagnosis. The result shows that the fault recognition rate of IFCM-CNN reaches 95%. The fault diagnosis effect is significantly better than other algorithms.
Modeling of UAV Integrated Logistics Support Process via an Agent-based Method
Authors: Zhang Q M , Hai X S 
Published: February 2021

Abstract
An agent-based integrated logistics support simulation and evaluation model for unmanned aerial vehicle (UAV) systems is proposed to meet the requirements of UAV system integrated support during mission execution. First, according to the typical mission execution process of a UAV system, the basic process of its use support and maintenance support is analyzed in depth. Second, considering the characteristics of multi-element function behavior, state transition and environmental change, the interaction relationship between agents is given, and then, a multi-agent model is established. Third, combined with the task execution process, a model evaluation algorithm based on the Monte Carlo method is proposed. Finally, the typical mission mode of a UAV system is selected to verify the model by taking the mission success rate and mission reliability as examples. The results show that the proposed model has enough flexibility and convergence speed and can support the analysis and evaluation of the UAV system integrated support process.
A preliminary mapping network model for unsafe acts in maritime accidents
Authors: Fu Shanshan , Zhuang Hui , Zhang Changjiang , Xi Yongtao 
Published: February 2021

Abstract
Unsafe acts are a critical issue causing maritime accidents. In order to explore the correlations between the crew’s unsafe acts and the induced maritime accidents, this paper proposes a preliminary mapping network model. Its first part is a hierarchical model, making crews’ unsafe acts as the top layer, skill-based failures, rule- and knowledge-based mistakes and violations acts as criteria, and basic unsafe acts (BUA) as the bottom layer. Therein, the BUAs are identified from 413 marine accident/incident investigation reports and 91 crews’ questionnaires. The second part is composed of several maritime accident types. The connection links between these two parts are aiming to reveal the correlations between each BUA and the specific maritime accident type. The proposed mapping network model can not only support unsafe acts analysis for one and multiple maritime accidents but also present the common BUAs for safety management.
The Influence of Water Content on the Acid Number of Diesel Engine Lubricant in Electrochemical Measurement
Authors: Zhou Fanhao , Yang Kun 
Published: February 2021

Abstract
Acid Number is one of the important characteristics of lubricating oil. In this study, thick film (TF) potentiometric sensors based on ion-selective electrodes (ISE) were used to determine the acid acidity of the diesel engine oil to determine the oxidation duration of the oil. This is a real-time online detection method. Two working electrodes (polymer electrode and glass electrode) and a reference electrode (bare Ag electrode) were fabricated, and the acid acidity of the diesel engine lubricant was expressed in the form of voltage, which overcomes the insufficiency of the titration endpoint in the titration method. Among oil products, most varieties only allow traces (water content below 0.3%) of moisture, and some oil products do not allow moisture. Water in oil can emulsify diesel engine lubricant, decompose additives, promote the oxidation of oil products. It affects the low-temperature fluidity of oil products. For transformer oil, extremely small amounts of water will seriously affect its insulation performance. In the experiment, the influences of water content for the acid acidity of the diesel engine lubricant were considered and tested.
The Influence of Nozzle Parameters on the Atomization Performance of Non-normal Fuel based on the Super-high Pressure Common Rail System
Authors: Liu Qi , Liu Yunsheng , Chen Xinzhuan , Huo Baiqi 
Published: February 2021

Abstract
The uniformity of the fuel and air mixture in the cylinder of diesel engine directly affects the smooth running of the combustion process. In order to improve the atomization effect of the fuel in the cylinder, the super-high injection pressure exceeding 180MPa was used. The changing relationship between the physical properties of the non-normal fuel and the pressure under the influence of the super-high injection pressure was derived. The three-dimension combustion model of TBD620 diesel engine is constructed on the FIRE software platform. A numerical simulation of the two injectors’ fuel injection process under different load conditions has been done in the research work. The fuel spray characteristics has been simulated. The results show that the special fuel injector has a good performance under low loading conditions, but the standard fuel injector has better performance for oil and gas fully mixed under high loading conditions.
INFLUENCE OF FEMTOSECOND LASER PROCESSING PARAMETERS ON THE SURFACE MORPHOLOGY AND WETTABILITY PROPERTIES OF POLYLACTIC ACID
Authors: Daskalova Albena , Angelova Liliya , Carette Xavier , Mincheva Rosica , Raquez Jean-Marie , Trifonov Anton , Buchvarov Ivan 
Published: February 2021

Abstract
Polylactic acid (PLA) is a very attractive material for applications in the field of regenerative medicine and tissue engineering, as it is a biocompatible and biodegradable synthetic polymer, whose morphological properties can be finely tuned via laser processing. Ultra-short pulse laser treatment is a non-invasive method for optimizing the surface properties of engineered biomatrices. The method offers controlled porosity of the treated biomaterial tailored specifically for implantation needs. In this research, we investigated the interaction of femtosecond laser radiation with PLA stacks while varying the output laser parameters in order to estimate their influence on the morphology of the PLA samples. The induced microstructural features were characterized by thickness measurements and SEM, EDX and FTIR analyses. In order to evaluate the hydrophilicity of the treated surface, water contact angle (WCA), measurements were also performed. Topography modification of the PLA substrates could essentially improve this material’s bioactivity properties, which, after proper optimization of the laser parameters, could make its biomedical applications even more successful.
Ultra-short laser pulse modification of chitosan/silver nanoparticles (AgNPs) thin films for potential antimicrobial applications
Authors: Iordanova E , Yankov G , Daskalova A , Dikovska A , Angelova L , Aceti D , Filipov E , Stanev G , Calin B , Zamfirescu M 
Published: February 2021

Abstract
The last several years witnessed increasingly rapid advances in applying biopolymers in tissue engineering for the purposes of regenerative medicine. The growing demand for preparing materials with desired physical, biological and mechanical properties requires active investigations in the field of tissue engineering. Among the wide variety of biopolymers, chitosan proved to be an outstanding material due to its properties, such as biocompatibility, biodegradability and a wide range of available fabrication technologies. The present work is a case study of an extensive research on the functionalization of thin biopolymer films via laser patterning. The aim of the current study is to investigate the optical properties of biopolymer films on the example of chitosan and chitosan with silver nanoparticles additives. As laser sources are used a nano- and a femto-second laser system emitting the wavelengths of 355 nm and 800 nm, respectively. The compositions produced are investigated by spectral analyses using spectrometers and an optical microscope. Furthermore, the morphology of the samples is monitored by SEM analyses. The results obtained demonstrate the potential of the method employed for obtaining diverse porous modifications depending on the laser parameters. Adding silver nanoparticles will drastically increase the thin chitosan films’ antimicrobial properties, thus enhancing the biocompatibility properties of the 2D matrices created.
Electron-beam surface alloying of Ti substrates with Ta films
Authors: Valkov S , Ormanova M , Bezdushnyi R , Petrov P 
Published: February 2021

Abstract
We report electron-beam surface alloying of Ti substrates with Ta. The Ti substrates were covered by a Ta coating with a thickness of 2 μm. The samples were alloyed by a scanning electron beam, with the beam deflection geometry in the shape of the infinity symbol (∞). Two experiments were implemented, where the width of the infinity symbol was kept constant at 8 mm, while the height was 8 mm for the first experiment and 4 mm for the second one. The phase composition of the specimens produced was studied by X-ray diffraction (XRD). The microstructure and chemical composition were investigated by scanning electron microscopy (SEM) and energy-dispersive X-ray spectroscopy (EDX), respectively. The results showed that the phase composition consisted of a double phase structure of α’ martensitic and of beta phases. Some amount of pure Ta remained in the alloyed layer produced by the first experiment. Also, the distribution of the alloying element into the substrate was significantly more homogeneous in the case of the second one.
Measuring, controlling and exploiting heterogeneity in optoelectronic nanowires
Authors: Al-Abri Ruqaiya , Choi Hoyeon , Parkinson Patrick 
Published: February 2021

Abstract
Fabricated from ZnO, III-N, chalcogenide-based, III-V, hybrid perovskite or other materials, semiconductor nanowires offer single-element and array functionality as photovoltaic, non-linear, electroluminescent and lasing components. In many applications their advantageous properties emerge from their geometry; a high surface-to-volume ratio for facile access to carriers, wavelength-scale dimensions for waveguiding or a small nanowire-substrate footprint enabling heterogeneous growth. However, inhomogeneity during bottom-up growth is ubiquitous and can impact morphology, geometry, crystal structure, defect density, heterostructure dimensions and ultimately functional performance. In this topical review, we discuss the origin and impact of heterogeneity within and between optoelectronic nanowires, and introduce methods to assess, optimise and ultimately exploit wire-to-wire disorder.