bluuebunny/crossref_metadata_2025_split huggingface dataset:
Damage Behavior of 30CrMnSiA Steel under Coupling action of Marine Atmospheric Environment and Tensile-compressive Load
Authors: Luo L Z , Zhou K , Li X F , Fu Z X , Teng J P 
Published: February 2021

Abstract
The coupling test of marine atmospheric environment and tensile-compressive load for 30CrMnSiA steel was carried out with the coupling test equipment of marine atmospheric environment and tension, compression and bending load. The damage behavior of 30CrMnSiA steel on the coupling action of marine atmospheric environment and tensile-compressive fatigue load was discussed. The metallographic results showed that the damage behavior characteristics of static test and coupling test were consistent. The decrease of tensile strength, proof strength plastic extension and percentage elongation after fracture of 30CrMnSiA steel were accelerated by the coupling action of marine atmospheric corrosion and tensile-compressive fatigue load. And the accelerated ratio of the coupling test was more than 10 times that of the static exposure test. The fracture morphology results showed that the fracture of the coupling test was corrosion fatigue fracture, and the cracks of 30CrMnSiA steel in the coupling test extended from the fatigue source to the core, forming directional corrosion fatigue damage.
Research on Health Management Technology and Application of Lifting Machinery
Authors: Liu Guansi , Ding Keqin , Jin Hui , Chen Li 
Published: February 2021

Abstract
Lifting machinery is a key facility for the development of modern industry. It’s not noly an important support for the construction of major national projects but also one of the core competitiveness of my country’s equipment manufacturing industry. With the development of large-scale, high-parameterization and intelligentization of lifting appliances, technologies such as safety monitoring and health monitoring have been gradually applied to industrial fields such as ports and metallurgy. In order to further develop the data-driven health management technology and engineering application of cranes, on the basis of elaborating the health management needs of cranes, the current status and development trends at home and abroad, we explored and proposed a technical framework for health management of cranes, and analyzed the lifting Key technologies such as machinery safety monitoring, health monitoring, health status diagnosis, failure trend prediction, and predictive maintenance decisions. Finally combined with a 200t casting crane in a steel plant, carried out safety monitoring and data-driven diagnosis, prediction and system visualization management. The results show that: the hoisting machinery health management system can monitor and monitor in real time and carry out early warning and forecasting to avoid the occurrence of unexpected accidents; based on predictive maintenance decisions, it helps enterprises to reasonably arrange maintenance cycles and maintenance methods to reduce the maintenance cost of the enterprise; reduce hoisting machinery downtime Time to enhance the effective value of assets; and enhance the level of enterprise information management.
Ply Parameters Optimization and Strength Reliability Analysis of Wind Turbine Blade
Authors: Yu Zelin , Sun Pengwen 
Published: February 2021

Abstract
As the critical component of capturing wind energy, the performance and reliability of blade are directly related to the safe, stable operation and service life of wind turbines. The performance of the blade is mainly determined by the ply parameters, so it has important valueto study the optimization method of ply parameters and the analysis method of strength reliability of wind turbine blade.In this paper, the load of a 1.5MW wind turbine bladeunder the DLC1.5g-2 working condition is calculated and its finite element model is established. Combined with engineering practice, the investigation range of ply parameters is determined, the test scheme is designed by using the mixed level uniform experiment method, and the blade strength is analyzed. Based on the polynomial regression analysis method and simulation results, the quadratic mathematical model between the ply parameters and the Tsai-Wu failure factors is established, and the range of ply parameters is optimized by mean value analysis method and interaction analysis method. On this basis, the ply parameters are regarded as random variables, and the structural performance function of blade failure is constructed. The reliability of the blade is predicted by the first-order second-moment method. The results show that the blade is reliable in the range of optimized ply parameters. The work provides the method and technical support for the laminate structure design and optimization of wind turbine blade.
Analysis of Low Temperature Compression Characteristics of Rubber Seal Strip of Shelter based on ABAQUS
Authors: Huang P , Wang Y S , Li Y , Tao J Y 
Published: February 2021

Abstract
The extreme low temperature of the alpine region is easy to have a bad effect on the sealing performance of the rubber seal strip of the shelter. In this paper, ABAQUS software is used to simulate and analyse the compression characteristics of the seal strip of the shelter at 23°C and -55°C, the Von Mises stress and the surface contact stress at two different temperatures are obtained. The result shows that the compression performance of rubber seal strip is sensitive to the extreme low temperature, and it is prone to low-temperature failure. The simulation results in this paper can provide an important reference for the subsequent low-temperature environmental test, so as to more comprehensively analyse the low-temperature failure mechanism of the rubber seal strip of the shelter in the alpine region.
Big Data Fast Analysis Method of Random Stress Spectrum for Crane Equipment
Authors: Ding Ke , Chen Li , Liu Guansi 
Published: February 2021

Abstract
With the increase of service time, the random stress spectrum of crane equipment causes cumulative damage. Cumulative damage induced crack initiation is one of the important failure modes of crane equipment. Through the rapid analysis of the random stress spectrum obtained in real time by the structural health monitoring system of lifting equipment, the cumulative damage of the structure can be analyzed and the remaining life of the structure can be predicted. In this paper, based on the traditional rain flow counting method, the big data fast analysis method of random stress spectrum is studied by adopting stack data structure. The program of fast rain flow counting method based on stack structure with two parameters is compiled. The fast rain flow counting method based on stack structure is used to analyze and calculate the big data of stress monitoring collected by the structural health monitoring system of metallurgical crane, and the stress amplitude-mean-frequency matrix of the hot spot area of fatigue damage of the main girder is obtained, which lays an important foundation for the health status diagnosis of metallurgical crane equipment.
A Deep Belief Network and Dempster-Shafer Theory Multiclassifier for Reliability of Wind Turbine System
Authors: Yu Bin 
Published: February 2021

AbstractObject. Reliability of wind turbine system could be made by predicting the status of power system in case it could remind engineers to fix in advance. There are multiple variables associate with system. An approach for classification according to these variables needed. Method. I proposed a deep belief network and Dempster-Shafer Theory (DBN-DS) by multiclassifier for whether wind turbine system needed to fix. DS would make a correct decision delete from DBN when model outputted incorrect result. And diagnose the wind turbine system to make a correct decision. Result. The new method was validated on wind turbine system data in 42-day intervals. The accuracy of SVM, KNN, MLP, DBN and DBN-DS were 95.1%, 96.1%, 91.2%, 97.0% and 97.5% respectively. Conclusion. This DBN-DS was more efficient that KNN, MLP, SVM and DBN. The performance was high because of binary Restricted Boltzmann Machines. The proposed method may be effective in decision support for diagnosing the wind turbine system.
Optimization of spline bearing capacity considering the influence of assembly sequence
Authors: Zhao Q Y , Yu T X , Song B F 
Published: February 2021

Abstract
Splines have been widely using in aerospace and other fields. Their reliability has important impact on the capability of mechanical equipment. When a slot on the internal spline is combined with different teeth on the external spline due to machining errors,, different tooth clearances are generated. Therefore, when the spline is assembled in different sequences, the loads on the spline teeth will be different, which can affect the bearing capacity of the spline. However, in the actual assembly process of the spline, this effect has not been considered. To overcome the issue as listed above, a method for optimizing spline assembly sequence is proposed. First of all, the calculation method of the tooth clearances depended on the spline assembly sequence is established. Then, a spline load distribution model is proposed, and the spline assembly sequence is optimized by the maximum clearance method. Compared with the traditional random assembly method, the results show that the mean value of the maximum nominal tangential force of the spline is reduced by 25%. The obtained results can be used to guide the high reliability design of the spline.
Research on Bearing Life Prediction Method Based on EMD and Gray Model
Authors: Hailong Ma , Zhen Li 
Published: February 2021

Abstract
In order to predict the residual life of bearing based on practical signals, the Empirical Mode Decomposition (EMD) is proposed and it is used to decompose the signal and filter out the invalid frequency components in the signal. The root means square (RMS) values of the pre-processed life cycle data samples were calculated. It is used to describe the health status of bearings and form a list degradation characteristic quantity. Then the list is used to train the Grey Model. The characteristic quantity trend is estimated by the trained Grey Model. It is verified by testbed and engineering practice. The results show that this method can predict bearing life effectively and with high precision.
Investigation of The Reliability and Sensitivity of the Wear Resistance of Ball Screws
Authors: Zhou Chang-Guang , Xi Jing-Yao , Chen Bin-Bin , Feng Hu-Tian 
Published: February 2021

Abstract
Based on the traditional Archard wear theory, a novel wear model of ball screws was established by considering the actual contact condition between the ball and the raceway. According to the stress strength interference theory and the improved first-order second-moment method, the model of the reliability and sensitivity of the wear resistance of ball screws was proposed. The numerical example of both the reliability and sensitivity of a typical miniature ball screw (1004) in a small satellite was presented. The unit sensitivity was defined and proposed to better indicate the influence of different parameters on the wear resistance of ball screws, based on which the 1004 ball screw was redesigned and the wear resistance reliability of the ball screw was improved by 21%.
Research on sampling schemes of Weibull distribution product life test
Authors: Li Zhewen , Shen Guixiang , Zhang Yingzhi , Mu Liming , Zheng Jun 
Published: February 2021

Abstract
According to Weibull distribution timing truncation test, considering that it is difficult to have a strictly defined complete failure samples in engineering practice, so the life sampling schemes of censored failure samples are discussed. Here, we have considered random right censored samples with different censored ratios. Compared with other sampling studies, this paper is not limited to explore more sampling theories, but uses SPSS software to give the specific operation processes of three sampling schemes: simple random sampling, two-stage sampling and Bayes sampling considering the minimum total cost, as well as the discussion on the verification analysis of the sampling accuracy. In order to simplify the estimation of Weibull distribution parameters, the estimated parameters are obtained by the probability plot analysis of Minitab software, thus the error between the sample’s MTBF (Mean Time Between Failure) and the overall MTBF is calculated. The sensitivity of Weibull distribution parameters is obtained by Minitab software. Finally, according to the accuracy of the three sampling schemes with different censored ratios, the optimal life sampling decision is obtained, which may provide sampling reference for the decision makers.
Ergonomics Optimization of Heavy Commercial Vehicle
Authors: Zhang S Y , Pang R Y , Liu C 
Published: February 2021

Abstract
Optimize the cab seat height of the heavy commercial vehicle and the maneuverability of the shift lever. Method: The mathematical model of human sitting posture and upper limb operation were established. The Chinese human body size was corrected by the combination of height growth rate and height linear ratio. Under the constraint of sitting posture, the H-point fitline model of the 5th, 50th and 95th percentile male drivers in China was obtained, and the optimal H-point range and SgRP point height were determined. The problem of high seat height has been optimized. At the same time, a operating lever layout position model is established; The actual measurement was made in the Class A vehicle, and the shift lever arrangement position was redefined. Conclusion: The height adaptability of the seat is improved; the operating comfort of the shift lever is improved; the visible area of the instrument panel becomes larger, and the 10th percentile male driver in China has a larger blind spot.
Evaluation and Optimization Strategies of Environmental Protection Performance for Passenger Seats of EMU
Authors: Jia Xu , Zhan Xue , Zhou Xinhong , Chen Chuanhai , Jin Tongtong 
Published: February 2021

Abstract
Passenger seats of Electric multiple-unit (EMU) influence environmental performance. Formaldehyde and other volatile organic compounds in the nonmetallic material of the seat is volatized. Toxic gas is produced by seat material combustion. This study chooses a typical passenger seat and proposes optimization strategies based on the experiment. First, the source of seat formaldehyde and volatile organic compounds is determined through a test. Four optimization strategies, including foaming pretreatment, foaming formula improvement, binder optimization, and bioenzyme spraying, are proposed. Second, the source of toxic gases in the seat is determined through a combustion test on the seat and its nonmetallic materials. Moreover, the optimization strategy for controlling the material of seat fabric is formulated.
Research on the Plan of Plane Line Replaceable Units Based on FSMC Model
Authors: Jiang Zi-han , Wang Zhuo-jian , Li Zhe , Li Yuan , Li Hao 
Published: February 2021

Abstract
The line replaceable unit (LRU) is a direct carrier of the fighter’s field replacement and maintenance strategy. It is reasonably and accurately divided into modules, which can quickly locate the fault location, reduce maintenance support time, and improve the efficiency of maintenance support Improve combat effectiveness. Aiming at the problem of the LRU division method in the aircraft design stage, this paper proposes an FSMC aircraft LRU division method based on function-structure-maintainability-coupling, comprehensively uses fuzzy clustering and other methods to evaluate and analyse the LRU division scheme, and compare different LRU schemes Use availability of the aircraft to perform simulation analysis. The research results show that the established on-site replaceable unit evaluation model can solve the problem of fighter aircraft LRU division schemes in the context of actual combat, and provide model support and empirical reference for further research on aircraft LRU division design research.
Study on Risk Assessment Method of Flight Operation Environment with SVR
Authors: Zheli Cai , Zixuan Wu , Weizhen Luo , linlin Li , Kaiye Gao 
Published: February 2021

Abstract
Flight operation control still can be improved in some aspects. For example, solve the problems of risk-related factors and complicated assessment methods in flight operation, reduce the potential risk caused by the difference of subjective judgment of personnel, and improve the airlines’ ability to control flight operating risks. In order to achieve these improvement, this study proposes an environmental risk assessment method for flight operation control based on support vector regression machine. The method includes the following steps: (1) firstly, the flight phases are divided; (2) secondly, the main environmental factors of each phase are determined and the data normalization rules are set according to business knowledge; (3) lastly, the model is trained with historical flight data from an airline company, to assess the environmental risk in take-off and landing phase during flight operation. The experiment results prove the validation and efficiency of the model which has been applied to flight operation risk assessment in practice.
Field Test of Online Leakage Noise Monitoring for Pressure Water Pipeline
Authors: Lin Tianxiang , Ye Guanlin , Feng Shaokong , Zhu Xinmin 
Published: February 2021

Abstract
In order to study the applicability of leakage noise (vibration) monitoring method, an online leakage monitoring test was carried out on a large pipeline. In the test, the emptying valve on the pipeline was used to simulate the leakage point, and the vibration signal caused by leakage was monitored by the hydrophone and other floating cables installed in the pipeline. By controlling the opening degree of the emptying valve, the different degrees of leakage between 10L/s and 105L/s was simulated, and the monitoring data for 10 minutes were recorded from 5 minutes before valve opening. The analysis results of the test data showed that although the environmental background of the monitoring was very disturbing, the leakage could be detected when the leakage degree was more than 0.05% of the pipeline flow. The monitoring results also showed that the noise caused by the leakage of large buried water pipelines was mainly transmitted in the form of vibration along the soil around the pipeline.
Research on reliability of cabin structure of a launch vehicle under road impact
Authors: Wang Teng , Han Rui , Qi Kexin , Zhang Yuxin , Gong Qi 
Published: February 2021

Abstract
A certain type of launch vehicle cabin not only bears the weight of the launching device, but also withstands the transient impact transmitted by the chassis, which is caused by the rough road. As an intermediate link, its structure should have sufficient strength and reliability. The structural strength of this type of cabin frame is simulated and calculated by using the finite element analysis method. The impact conditions are identified to ensure that the simulation input shock conditions can cover the actual impact situation through driving experiment. The simulation results show that the structure is reliable and the structural performance meets the requirements.
A remaining useful life prediction method for complex systems based on multi-index fusion with MC and HSMM
Authors: Zhang D F , Ran Y , Zhang G B , Jin C X , Li S L 
Published: February 2021

Abstract
Remaining useful life (RUL) estimation is the core and basic of system Prognostic and Health Management (PHM) and also a challenging for complex systems. It is necessary to use performance indicators that are closely related to system status for analysis, due to the Multi-indicator different characterization change of system degradation, different detectability and the degree of correlation caused by system coupling. As the system status degradation shows certain scientific laws in macro, their would be certain random relationship between the system status degradation and RUL. To address these problems, the concept of imperfect condition monitoring followed by the concept of key performance indicators in order to reduce the blindness of analysis object selection. The condition degradation probability index is proposed to represent the status degradation degree of the system, whose future trend is fitted by Markov matrix obtained by the improved algorithm as a implementation of mapping condition monitoring data to CDPI. Finally, the system RUL estimation method at time t combined the hidden semi-Markov model with improved forward variable is given to realize the mapping CDPI to RUL. Experiments are carried out to validate the key concepts of the developed methods, and results suggest the effectiveness.
Optimization design of shaped charge based on improved genetic algorithm
Authors: Tang Cheng , Xue Biao , Wang Li-Xia 
Published: February 2021

Abstract
In order to improve the design efficiency of shaped charge, reduce the number of tests and shorten the development period, an improved genetic algorithm is introduced in the design process of shaped charge. Compared with the design scheme in the iterative process of traditional optimization design, the improved genetic algorithm introduces the multi parent crossover operator, randomly selects N individuals, forms the subspace, and hybridizes N individuals in the subspace to form a new individual. Because of the number of individuals involved in the hybridization, it is easier to calculate the optimal solution, and has stronger optimization ability. Taking a shaped charge as an example, the structural parameters of shaped charge are optimized by the improved genetic algorithm. After the optimization, it is verified by the vertical static armor breaking test of shaped charge, The results show that the optimization design method of shaped charge structure based on the improved genetic algorithm is reasonable and feasible, and the operational and technical indexes of the optimization scheme meet the requirements.
Fleet Maintenance Strategy Planning with Time Windows Integrated with Multi-Agent and Wolf Pack Reinforcement Learning
Authors: Xinrui Ma , Haixu Li , Zheng Zhou , Bo Chen 
Published: February 2021

Abstract
Selective maintenance is a widely used strategy to identify and perform the maintenance actions necessary for fleet mission success. Aiming at the problem of maintenance strategy planning with time windows (MSPTW) which is common in short-term operation plan, a fleet maintenance strategy planning approach based on multi-agent and reinforcement learning is studied in this paper. Based on the four kinds of foraging behaviors including migration, summon and attack in traditional Wolf Pack Algorithm (WPA), the intelligent behavior is redefined, and a new wolf pack algorithm for solving the MSPTW is designed. In order to seek the best path planning, a mathematical model with the aim of minimizing the total cost (fixed cost, transportation cost, waiting cost and penalty cost) is constructed utilizing the fitness and penalty function.