bluuebunny/crossref_metadata_2025_split huggingface dataset:
Pipeline volumetric defect assessment method based on multi risk factors and in-line inspection data
Authors: Ling J T , Dong S H , Zhang H 
Published: February 2021

Abstract
Volumetric defects in pipeline is one of the main factors causing pipeline leakage accidents. Once an accident occurs, it will cause huge economic and environmental loss. At present, the assessment of pipeline volumetric defects in existing standards is only calculate the residual strength of pipeline by defect size (length, width, depth), without considering the influence of other external risk factors. Therefore, defect-related risk factors were introduced when calculating the residual strength of defects using in-line inspection data. Due to the massive data resources produced during the construction and the operation period, a risk factor correlation analysis model for extracting the risk factors related to the pipeline safety was established. The weight of each factor is obtained by using analytic hierarchy process algorithm, and a new defect risk index was put forward. Therefore, the volumetric defect assessment method based on multiple risk factors of defects and in-line inspection data is proposed. The result of on-site examples shows that the defect assessment method proposed in this paper can reflect the true safety status of the defects, it can also provide support for scientific and reasonable pipeline maintenance decision.
Reliability evaluation method of LED lighting matrix considering degradation and catastrophic failure
Authors: Gu Changchao , Li Lexiao , Ye Nanxin , Chang Hao 
Published: February 2021

Abstract
Aiming at the current situation of degradation and catastrophic failure of weaponry, a reliability modelling method considering performance degradation (lumen degradation) and catastrophic failure (nonluminous) is proposed with LED lighting matrix as the research object. First, for the degradation of lumen, the failure mechanism analysis is carried out, the thermal resistance model of lighting matrix and radiator is established, and the overall model of the degradation of the LED lighting matrix is realized. For the catastrophic failure, based on the uncertainty of the logic relationship of catastrophic failure of lighting matrix and the polymorphism of individual fault events, the method of combining fault tree and Bayesian network is used to realize the analysis of failure evolution and reliability modelling. Finally, the validity of the proposed method is verified with a case study.
Fault diagnosis of rolling bearing based on empirical mode decomposition and convolutional recurrent neural network
Authors: Huang Mulin , Huang Tingting , Zhao Yuepu , Dai Wei 
Published: February 2021

Abstract
Bearing is more important in mechanical parts. Many failures of rotating machinery are caused by bearing failure. It is very important to diagnose the rolling bearing fault and help the mechanical products to find out the failure of parts in operation. It can avoid danger and improve efficiency. To research the problem of rolling bearing fault diagnosis under different loads, a method using vibration signals based on empirical mode decomposition (EMD) and convolutional recurrent neural network (CRNN) is proposed. First, the EMD is used to deal with the vibration signal for noise reduction. Then, CRNN is built as the rolling bearing fault diagnosis classifier using the envelope of EMD processing. The Case Western Reserve University data sets are used to validate the method. The result shows that the method fits well.
Improved response surface method based on triple weighted regression
Authors: Wu Jie , Zhang Jianguo , You Lingfei , Ye Nan 
Published: February 2021

Abstract
The response surface method (RSM) is frequently used to reduce the computational burden of structural reliability analysis. In this paper, an improved RSM is proposed. The response surface is fitted by the triple weighted regression technique, which integrates weighting systems to assign weight factors to each sampling point including (1) the absolute value of the limit state function (LSF), (2) the value of the joint probability density function and (3) the distance from the design point. Numerical examples are presented to demonstrate that the proposed method gives more accurate results than RSM for both probability of failure (PoF) and LSF evaluations.
Structural reliability analysis with temporal and spatial variations based on polynomial chaos expansion
Authors: Nan Hang , Li Hong Shuang , Xue Cai Jun 
Published: February 2021

Abstract
Performance of engineering structures varies with time and space due to the uncertainties in time and space domain. This paper presents a polynomial chaos expansion (PCE) based method to evaluate the reliability problem with temporal and spatial variations. The sequential quadratic programming (SQP) is employed to obtain the samples of spatial response extreme value at discrete time instants, and then the surrogate model of spatial response extreme value can be constructed by PCE based on those samples. Therefore, the structural response hypersurface in time and space domain is transformed into a trajectory of spatial response extreme value in time domain and the reliability analysis can be achieved by Monte Carlo simulation (MCS). Three examples are used to demonstrate the performance of the presented method in accuracy and efficiency.
Application of BP Neural Network and Convolutional Neural Network (CNN) in Bearing Fault Diagnosis
Authors: Deng Hai , Zhang Wan-xuan , Liang Zheng-feng 
Published: February 2021

Abstract
The convolutional neural network (CNN) identification method and the BP neural network identification method were used to diagnose the bearing fault respectively. When using the CNN diagnostic method, first perform continuous wavelet transform (CWT) on the vibration signal of the rolling bearing to obtain a time-frequency map, and then compress the time-frequency map to an appropriate size; Then, the compressed time-frequency map is used as a feature map to input into the CNN classifier model established; finally, an experimental study is carried out based on the artificial bearing fault data set of Western Reserve University. The results show that the average accuracy rate of this method is greater than 99%.In the BP fault diagnosis method, based on the data set, nine parameters of average value, maximum value, minimum value, peak-to-peak value, root mean square value, standard deviation, variance, skewness and kurtosis are established as training input vectors. Using BP neural network with 10 hidden layer nodes for fault identification, the results show that the average accuracy of identification is 93.7839%. The comparative analysis of the two methods shows that the BP identification method has higher training efficiency and takes less time; the CNN identification method has higher recognition accuracy, but the training takes more time.
Influential Parameter Analyses for Sinking Velocity with Measured Data
Authors: Xue X F , Feng Y W , Du Q Y , Lu C 
Published: February 2021

Abstract
To study the effect of operational parameters on the sinking velocity of the landing gear of carrier-based aircraft, the influential analyses of various related parameters were performed based on the measured data of F/A-18. The probabilistic statistical characteristics of the sinking velocity were firstly investigated. And then correlation coefficient method and Levenberg-Marquardt (LM) algorithm were applied to finish influential parameter analyses. The analysis results show that the important influential parameters are aircraft glide angle, deck pitch angle, approaching velocity and engaging velocity; the mathematical model of sinking velocity is established by LM algorithm, and the determination coefficient is calculated via the variance analysis, which reveals that the proposed regression model is good. Compared with the measured data, the average errors for the predicted values of the established model of sinking velocity are less than 5%, which validates the effectiveness and feasibility of the method in engineering practice. The present efforts provide a way to study the relationships of the sinking velocity and the related influential parameters. And this work was proved to be a useful method for the study of sinking velocity.
Characterization of surface crack width in plates using Rayleigh wave electromagnetic acoustic transducers
Authors: Ahmad Mubarak , Liu Zenghua , Basit Abdul , Bin Wu , He Cunfu 
Published: February 2021

Abstract
Surface crack in the plate like structures is one of the initial indication for its degradation. This indication could be very critical and requires some serious maintenance because this continuous exposure will lead to a severe damage to the safety and even to environment. To evaluate the structural performance and safety, a regular monitoring of such cracks is needed. A quantitative characterization method is utilized for the estimation of surface groove width instead of depth or length, which is previously done by many researchers, using Rayleigh waves in pitch-catch mode using electromagnetic acoustic transducers (EMATs). The method employs the experimentally determined reflection coefficient and transmission coefficient of Rayleigh waves scattered at a surface groove by a number of varying widths, which are compared to the reference curves, obtained from two-dimensional finite element method (2D-FEM) simulations for the same groove width as used in experiments. A good relation between FEM results and experimental results is found. Two different EMAT couples of different centre frequencies were employed to explore the measurement, and to compare and analyse the quantitative characterization of different groove widths. Both the FEM results and experimental results are compared and verified for the different groove widths. This comparison shows some percentage of error for the groove width ranging from 0.3 mm to 1.8 mm.
Demand analysis of quadcopter based on QFD
Authors: Nan Xiang , Lin Huo , Di Gai , Zhenhao Lv , Yikuan Li 
Published: February 2021

Abstract
The quality and safety of quadcopters have always been the focus of attention in the drone industry. Carrying out safety and functional requirements analysis for it can better meet customer needs, reduce design costs, improve reliability and safety, and provide ideas for product design updates. This article uses the QFD (Quality Function Deployment) method to transform the safety and functional requirements of the quadcopter into product design, and provides guidance and reference opinions for improving product quality and safety. Based on the analytic hierarchy process, the article determines the technical difficulty through the analysis of technical characteristics, and analyzes the functional and safety requirements of the quality house model constructed after the improvement of the four-axis aircraft to provide a basis for the improvement of the quality characteristics of the four-axis aircraft.
Comprehensive safety evaluation of metallurgical crane based on AHP and entropy weight method
Authors: Cheng J M , Zhang W M , Jin H 
Published: February 2021

Abstract
The determination of safety evaluation weight of most engineering equipment mainly depends on the subjective experience of experts, which ignores the objective requirements of indicator status evaluation, is unable to satisfy the needs of the evaluation system with the advances in modern equipment health monitoring technology. Hence, the authors establish a safety evaluation model to form a comprehensive weight using experience factors, based on the objective weighting of the entropy weight method (EWM) and the subjective weighting of the analytic hierarchy process (AHP), to integrate the objective analysis data and subjective prior knowledge. Then, a safety evaluation system with state value as the main consideration was built on the combination of knowledge and fuzzy comprehensive evaluation. Finally, the availability of the proposed evaluation method was verified by the example.
Simulation analysis of outage recovery time of navigation satellite
Authors: Zhao Haitao , Xiong Xiao , Wang Qinghua 
Published: February 2021

Abstract
Outage recovery time is an important factor affecting the availability of navigation satellite. In order to effectively estimate the outage recovery time of satellite on orbit at the design stage, this paper analyses the specific process of outage recovery, and puts forward the modelling and analysis method of outage recovery time according to the characteristics of outage recovery process. In this paper, outage recovery time is divided into fault detection time, fault location time, fault handling time, state recovery time and access system time. By using the correlation analysis method, the equipment that may cause outage can be located quickly. Taking the recovery time corresponding to a certain recovery strategy as the input, the recovery time on the satellite can be obtained by weighting the recovery time and failure rate. Considering the randomness of outage recovery process, state flow graph is used to model and simulate the recovery time. Finally, an example of simulation analysis is given.
Reliability design of aerospace secondary power supply based on fault tree analysis
Authors: Gao Ting , Liu Mi , Qu Hong-Yi , Ji Hong-Juan , Jing Jiang 
Published: February 2021

Abstract
As the satellite power supply and distribution functions and complexity are gradually strengthened, the reliability requirements of the aerospace secondary power supply are getting higher and higher. Based on the basic composition and working principle of aerospace secondary power supply, this paper analyzes the reliability of the fault tree analysis method (FTA), combs the weak link of the product, and proposes design improvement measures for the weak link.
Gear Fault Diagnosis Based on GPU-CNN
Authors: Dong Zhipeng , Meng Shuo , Chi Kuo , Kang Jianshe 
Published: February 2021

Abstract
Gear is widely used in mechanical transmission system, but it is prone to failure, which seriously affects the performance of equipment. In order to realize the diagnosis and classification of gear faults, we used Convolutional Neural Networks (CNN) to extract time-frequency image features of its vibration signal. CNN can extract the characteristics of time-frequency signals from vibration signals and identify gear faults accurately. However, due to the large training data set, CNN training costs too much time. According to the characteristics of Graphics Processing Unit (GPU), Compute Unified Device Architecture (CUDA) can improve the speed of CNN algorithm and reduce the time consumption. Therefore, this paper proposes a method based on GPU-CNN for gear fault diagosis. The experimental results show that the method can effectively shorten the training time and significantly improve the operation efficiency.
Dynamics and reliability analysis of the deployment process of spring folding wing
Authors: Gao Yun , Hu Ming , Zhao Deming , Gao Xingwen , Lin Jiangfeng 
Published: February 2021

Abstract
A “X” type spring folding wing is taken as the research object in this paper, and schematic diagrams of unfolding and locking process are drawn according to its structure and working principle. The theoretical model of kinematics and dynamics which considering the gravity moment is established by simplifying the geometric model of deployment mechanism of the folding wing, so the curve of deployment angle and angular velocity of the outer wing during the deployment process can be obtained. The pulley diameter, preload force and stiffness of the spring-actuated are taken as random variables, and the deployment time and angular velocity are regarded as evaluation indicators. The Monte Carlo method is used to analyse the reliability of deployment process of the folding wing, and the reliability of the deployment process is obtained. The results show that the reliability of the deployment process of the spring folding wing is high.
Research on Civil Aircraft Cabin Service Availability Analysis and Application
Authors: Gao Weiyan , Lu Peng 
Published: February 2021

Abstract
Reliability is one of the important characteristics of civil aircraft, it is an important factor to ensure flight safety and high punctuality, and to obtain good economy. The cabin service availability analysis is a key segment in the overall reliability analysis. This paper focuses on ddetermination principle of functions related to cabin service availability and the judgment of failure effects and other contents, and establishes a civil aircraft cabin service availability analysis method and analysis process.
Research on mission reliability and sensitivity of folding tail mechanism
Authors: Pang Huan , Shi Dongyang , Wang Daocheng 
Published: February 2021

Abstract
Folding tail mechanism is widely used in subsonic and super/high sonic missiles, and its mission reliability is directly related to the success or failure of missile launch. Taking the torsion bar folding tail mechanism as the object, the failure modes and failure influencing factors in the mission process are analyzed systematically. The dynamic model of the folding tail mechanism is established. According to its characteristics, the multi-stage correction method of the dynamic model is proposed and realize the high-precision simulation. Finally, the mission reliability and sensitivity analysis is carried out, and the reliability sensitivity of folding tail mechanism is obtained, which lays the foundation for reliability optimization.
Optimization Of The Measurement Precision Consistency Of Single-Phase Smart Electricity Meters In Full Temperature Range
Authors: Ye Xuerong , Lyu Mingdong , Sun Qisen , Yuan Ruiming , Li Wenwen 
Published: February 2021

Abstract
With the development of smart power grids, smart electricity meters are widely applied to industrial production and the life. For interests of the power supply and consumption parties, electricity meters are required to have high quality, precision and consistency. As temperatures vary considerably in south and north of China and electricity meters work in complex temperature environments, studies on the effects of temperature on power metering are of significant importance. In this paper, an optimization method considering the effects of temperature is proposed for the consistency of electricity meters. The precision consistency of electricity meters is optimized in full temperature range through means such as electrothermal coupling simulation, orthogonal test, cost calculation, etc., and the design scheme of electricity meters with maximum cost performance can be delivered for their manufacturers.
Research on the application of clustering and classification in battlefield damage identification
Authors: Song Mingchang , Shi Quan , Yin Shizhuang , Li Lei 
Published: February 2021

Abstract
This paper explores the solutions to the problem of battlefield damage pattern recognition. The main research results of the two components of clustering and classification are discussed respectively, and the main characteristics and existing problems of the existing methods are analyzed. The advantages, disadvantages and application scope of different methods are described in detail, which provides a basic theoretical guidance for the study of battlefield damage identification.
Brief Discussion on Evaluation & Demonstration of Operating Reliability of Safety-level I&C System Equipment in Nuclear Power Plant
Authors: Zhu Guixia , Qian Yugang , Lan Jian , Li Diliang , Zhou Tianmi , Hu Yuying 
Published: February 2021

Abstract
Safety-level system equipment is essential for the nuclear power plant either to complete the reactor emergency shutdown, containment isolation, reactor core cooling and heat emission from containment and reactor, either to prevent large amounts of radioactive substances from being released into the environment, and is also the focus of system equipment reliability management. As the safety-level system equipment has seismic requirements, in this paper, the operating reliability of safety-level I&C system equipment is evaluated and demonstrated, and the general process of reliability evaluation & demonstration is worked out.
Study on failure of transmission shaft based on finite element and fracture analysis technology
Authors: Xia Ming , Zhao Ke-lun , Zhao Hai-xin , Yang Jing 
Published: February 2021

Abstract
Due to the harsh driving environment, the power transmission components of military vehicles are subjected to long-term alternating loads and sudden impact loads. A failure analysis of the transmission shaft of a military truck was carried out. By constructing a mechanical simulation analysis model of the transmission shaft, the dynamic response of the structure under alternating stress and impact load is solved. Then the cause and mechanism of drive shaft failure were analyzed. Using fracture analysis technology to discuss the phenomenon of bearing sleeve cracking, circlip rupture and flange fork deformation. It indicates that caused by overload, foreign matter between the shaft and the needle etc., which ultimately leads to the failure of the universal joint transmission. Finally, the optimal design of the drive shaft is proposed.
A Fault Diagnosis Method based on Improved Synthetic Minority Oversampling Technique and SVM for Unbalanced Data
Authors: Han MingHong , Wu Yaman , Huang Yunfeng , Wang Yumin 
Published: February 2021

Abstract
Equipment usually breaks down suddenly and irregularly, so most of the data sets obtained for fault diagnosis have unbalanced characteristics, and the amount of data varies greatly from different fault types. In this paper, three problems in the application of synthetic minority oversampling technique (SMOTE) are studied, and the improved SMOTE algorithm combined with support vector machine (SVM) is proposed. The validity of the model is verified by CWRU bearing data compared with SVM and SMOTE+SVM methods, and the result of fault diagnosis is satisfactory.
Research on Reliability Life Evaluation of Torque Motor based on Performance Degradation
Authors: Ming Zhimao , Yang Jing , Zhao Kelun 
Published: February 2021

Abstract
The torque motor problem of reliability. The reliability evaluation of torque motor under the condition of accelerated degradation test is studied. Firstly, the failure mechanism of torque motor is studied, the performance degradation parameters are determined, then the theory of accelerated degradation test is described, the type of accelerated degradation model and the conditions of accelerated test are described. The method and procedure of product reliability analysis using accelerated degradation trajectory method under accelerated degradation test are studied. Finally, the reliability of a torque motor is evaluated and the average life value above 0.9 is calculated
Influence factors and identification of state-of-health for traction battery
Authors: Li D , Zhimao M , Mingsheng C , Jin D 
Published: February 2021

Abstract
According to state of health parameters and management system function, the properties of parameters are detailed to satisfy requirements of electric equipment for traction battery. The result shows that: many parameters, such as the ways of charge and discharge, temperature and state of charge, have apparently effect on state of health in propulsion battery. Battery cycle life reduces obviously when much depth of discharge is applied. Low temperature limits attenuation morphology of power battery. And high temperature weaken solid-electrolyte interface. Different types of battery agree with specific law during capacity reduction. Based on battery power, resistance and reduction characteristics, it should be considered in battery health management research, which includes identified parameters and accurate equivalent model.