bluuebunny/crossref_metadata_2025_split huggingface dataset:
Design of orange grading system based on real time image processing
Authors: Ifmalinda  , Andasuryani  , Putri I 
Published: February 2021

Abstract
Orange is one of preference agricultural products by consumers, because it has several benefits suchas vitamin C and antioxidants. The fruit is often used for gift when someone visits the relatives, thus the quality of orange is mostly detected by visual suchas size and skin color of the fruit. Determination of the quality is done manually because it takes faster. The manual grading has the weakness and less effisien, resulting several quality gradings and needs man power more. Using the man power tend to be subjective judgement. One of the ways to increase the productivity to determine the orange quality is that using grading methode using technology real time digital analysis mechanically. The aims of the resarch is to design of grading machine and grading program based on diameter and skin color of the orange that analysed by real time image processing. Based on the research result, this system can be applied on orange grading. The capacity of the manual grading is 1,276 fruit/hour,meanwhile capacity of the grading system is 712.87 fruit/hour. From the speed of the process and grading capacity, the manual methode is better instead of grading system using image processing. Meanwhile for the quality of the grading, Using the grading system based on the image processing can be said that it is suitable toward the standard. If using manual grading, it use the principle of habit, without really measure specifically and detail.
Effect of various drying methods on the physical characteristics of purple yam powder
Authors: Nugraheni N F , Karyadi J N W , Tarwaca S N , Indrasari Y P , Albyan R , Setiyadi I , Ayuni D 
Published: February 2021

Abstract
Purple yam (Dioscorea alata) is a type of plant that grown in almost all regions of Southeast Asia. In Indonesia, purple yam is one of the most popular types of sweet potatoes compared to other types of the genus Dioscorea. Purple yum is usually consumed directly as a side dish, or processed into a powder. One important process of making purple yam powder is drying. In this study, the characteristics of purple yam powder were evaluated from several drying methods, namely sunlight drying (SD), cabinet drying (CD), and pneumatic drying (PD). The pneumatic dryer used was self-made with a stainless steel plate (3 mm thickness) and has total dimension of 1600x 500x 2500 mm. The results showed that the CD sample had the lowest water content. The purple yam powder by CD and PD can produce brighter powder compared to that with SD method. From the FM test, the smallest FM value was obtained from CD sample. CD sample proven to be able to retain purple yam nutritive values after drying process.
Precision agriculture: automated irrigation system in tandem with solar panels for melon farming cultivation
Authors: Nasution I S , Munawar A A , Devianti  , Satriyo P , Gunawan H G , Yunus Y 
Published: February 2021

Abstract
This present study aimed to design and apply an automated irrigation system powered by solar panels for melon farming cultivation. It related to precision agriculture practices from which benefited as an environmental friendly approach. This study was performed by designing irrigation systems, constructing solar panels as a power source for generating pump used to irrigate melon orchard. The results showed that those combinations setup were benefited to reduce manual irrigation system which is normally conducted by human efforts. Further, it also acted as an environmental friendly practice since the system is attempted to utilize solar energy as main power source for irrigation pump. Based on obtained results, it may conclude that abundance energy in our earth can be used for precision agriculture practices with the aim to reduce environmental pollution and waste.
Fitting Method of Small Sample P-S-N Curve Based on Weibull Distribution
Authors: Huang T , An Z W , Ma Q , Han M Q 
Published: February 2021

Abstract
In order to obtain the probabilistic stress-fatigue life curve of materials with small samples, a small sample P-S-N curve fitting method is proposed. This method is based on the premise that Weibull distribution can be applied to fatigue test data the method first uses the sample mean fitting to obtain the median S-N curve. Secondly, constructs the random variable function based on the Weibull distribution characteristics, in addition, the sample median is used as the initial value of iteration to perform perturbation optimization to determine the shape parameter a and the scale parameter β of Weibull distribution. The fitting of P-S-N curve is realized. Taking the fatigue data of aluminum alloy 2425-T3 as an example, the results show that the intercept relative error and slope error are less than 0.5% by comparing the fitting results of the proposed method with those of the traditional method, and the intercept error between the proposed method and the traditional method is less than 1.5% and the slope error is small when designing three groups of small sample fitting schemes (7-7-7-7, 5-5-5, 3-3-3) at 3.0%. The proposed method can obtain high-precision P-S-N curve fitting results in the case of small samples, which have a certain significance for engineering applications.
Research on Multi-Agent Task Optimization and Scheduling Based on Improved Ant Colony Algorithm
Authors: Wang Y , Yang R R , Xu Y X , Li X , Shi J L 
Published: February 2021

Abstract
As a key problem of cloud computing, the performance of task scheduling strategy may seriously affect the efficiency and service quality of the system. With the purpose of achieving balanced task scheduling with optimal completion time, ant colony optimization (ACO) algorithm is adopted as task scheduling strategy in this paper. Considering the problem of premature convergence to local optimal solution of ACO, an improved Max-Min Ant System (MMAS) is introduced to find the global optimal solution. Based on the study of pheromone’s updating mechanism of MMAS, MMAS is applied as task scheduling strategy with reasonable mapping from the objective of shortest path to shortest completion time. The task scheduling strategy based on MMAS has been simulated from views of tasks’ number, size and load balance, and the results shows that MMAS task scheduling strategy is with a better performance on completion time and load balance than ACO based strategy.?
Study on the Development of I&C Equipment Performance Monitoring Program for Nuclear Power Plants
Authors: Qian Yugang , Zhou Shumin , Hu Jiacheng , Zhu Guixia , Hu Yuying 
Published: February 2021

Abstract
The equipment performance monitoring program is designed to provide guidance for monitoring the performance of equipment, with an aim to enable engineers to identify hidden hazards as early as possible and take corresponding corrective actions to achieve the purpose of equipment reliability management of nuclear power plant. The nuclear power plant realizes monitoring, control and protection of the whole plant through I&C equipment, by which to ensure the safe, reliable and economic operation of the nuclear power plant. In this paper, a set of performance monitoring program process special for I&C equipment of nuclear power plant is developed. And the RGL system (rod control system and rod position system) of a nuclear power plant is taken as an example to illustrate, analyze and summarize, which lays a foundation for nuclear power plant to carry out equipment reliability management.
Remaining Useful Life Prediction Using Deep Multi-scale Convolution Neural Networks
Authors: Ge Y , Liu J J , Ma J X 
Published: February 2021

Abstract
Accurate Remaining useful life (RUL) prediction is the premise of system prognostics and health management (PHM). In fact, it is often difficult to predict the accurate RUL because of the diversity of working condition and self-state between systems. In this paper, a data-driven method is proposed for RUL prediction using deep multi-scale convolution neural networks (DMSCNN), which is made up of four convolution layers. Two of the four convolution layers are multi-scale convolution layers, which are composed by three different scales convolutions connected by deep concatenation layer. After the four convolution layers, we add fully connected layer and regression layer to build a deep learning structure for predicting RUL. The IEEE PHM 2012 data challenge bearing dataset is employed to verify the proposed method. The experiments result show that the proposed DMSCNN has better performance and higher prediction accuracy than other methods. Additionally, the t-distributed stochastic neighbour embedding (t-SNE) dimension reduction method is used to reduce the computation. Experiments result demonstrate that the features processed by t-SNE have better distinguishability, and the prediction accuracy can be further improved by inputting the t-SNE features into the DMSCNN proposed in this paper for RUL prediction. This paper offers a new and effective approach for RUL prediction.
A Birnbaum Importance and regression analysis based heuristic algorithm for multi-type component assignment problem
Authors: Guan Zhiling , Shi Yida , Qiu Siqi 
Published: February 2021

Abstract
In this paper, a new kind of multi-type component assignment problem (MCAP) called the two types of component of component assignment problem (TCAP) is proposed. The problem is to assign two types of components to three types of positions in a system in order to obtain high system reliability. The number of each type of components equals the number of positions in the system where the components can be placed in. A new heuristic algorithm, called the REG-ZK method, based on Birnbaum Importance and regression analysis for solving the new MCAP, is illustrated in the paper. Comprehensive numerical experiments on small systems and large systems are conducted to evaluate the optimization effect of the method. Compared to the enumeration and randomization method, the REG-ZK method proves to be applicable and efficient with good optimization quality.
Research on computer application software monitoring data processing technology based on NLP
Authors: Wang J , Liu B J , He W , Xue J K , Han X Y 
Published: February 2021

Abstract
In the process of using computer application software, the system may fail because of software defects. During the operation of the computer system, the running state of the system is also monitored. This paper mainly studies the monitoring data processing technology of computer application software based on NLP and presents a software monitoring data processing scheme based on NLP. First, the data were preprocessed by word segmentation and data cleaning. Then the named entity recognition and extraction information are accomplished by fusing CRF and rule-based methods. It can provide effective data support for system failure prediction by characterizing the software monitoring data.
An efficient global reliability analysis method for turbine disc’s multi-failure modes considering importance distribution technology
Authors: Liu Yu , Liu Xi , Hu Dianyin , Wang Rongqiao 
Published: February 2021

Abstract
This paper presents an improved efficient global reliability analysis (EGRA) method for a turbine disc considering the importance distribution of multi-failure modes, such as low cycle fatigue (LCF) and creep-fatigue (CF). Failure mode effects and criticality analysis (FMECA) technology is firstly used to analyse the criticality and occurrence probability of each failure mode. Importance factor S is then proposed to quantify the importance of the corresponding failure mode. In order to improve the reliability analysis’s efficiency, expected feasibility function (EFF) criterion in sequential sampling method is selected through numerical experiments to generate the samples of random variables. Secondly, EGRA method is established by combining sampling method with Kriging model, in which the performance function is fitted using the key sampling points near both the failure boundaries and high uncertainty region. On the basis of EFF criterion, the composite EFF criterion applied to EGRA method is developed. This method avoids repeated analysis on non-significant failure modes, which further improves the reliability analysis’s efficiency for the multi-failure modes system. Through a binary nonlinear example, it is proved that the prediction accuracy is 99.8% compared with Monte Carlo method. Moreover, the computational time of reliability is reduced by half compared with EFF criterion, which proves the prediction efficiency of composite EFF criterion. Finally, the reliability analysis on a turbine disc is conducted using the improved EGRA method combining with the failure mode importance distribution technology. Results show that the fatigue life at 99.9% reliability is decreased by 7.4% after considering the importance of failure modes, indicating that the ignoration of failure modes’ importance would lead to a more dangerous prediction result.
Reliability analysis and optimization of production system for production scheduling
Authors: Duan Weiwei , Dai Wei , Wang Yue , Sun Jiahuan 
Published: February 2021

Abstract
Production planning and scheduling mainly solve the problems of multi-process, multi-resource scheduling and sequence optimization in the workshop. Existing production scheduling methods focus on how to minimize the production period, but production system reliability is seldom considered in the actual production scheduling strategy. Production system reliability is closely related to the state change of equipment in production system, the production stability and efficiency. Therefore, in order to ensure the reliability of the production system when planning production tasks, this paper proposes a new strategy for production scheduling. Firstly, the model of production system is conducted to analyses its reliability. Secondly, a reliability evaluation method is proposed by analysing the status of equipment in the production system. Moreover, the optimization goal of production system reliability is added to the original production scheduling goal. Finally, the optimization method is put forward and verified by an example.
Bayesian Inference for General Half-Normally Distributed Lifetime Products
Authors: Xin Hua , Liu Tingting , Liu Zhifang 
Published: February 2021

Abstract
The generalized half-normal (GHN) distribution has earned widely concerned in reliability analysis. Type-I hybrid censoring (HC-I) is one efficient scheme for saving test time and cost to collect lifetime information of reliable products. However, the HC-I scheme also induces a complicated likelihood function and makes the searching of maximum likelihood estimates of the model parameters difficulty. In this study, the maximum likelihood estimation and Bayesian estimation procedure are studied for the GHN distribution based on HC-I samples. The Markov chain Monte Carlo approach using the Metropolis-Hastings algorithm via Gibbs sampling is proposed to implement the Bayesian estimation procedure for obtaining the Bayes estimators of the model parameters. The Bayesian estimation procedure is more reliable than the ML estimation method due to the Bayesian estimation procedure does not use gradient methods to search the estimates of model parameters. Simulation results show that the proposed Bayesian estimation procedure perform well in terms of the bias and mean square error.
Research on solder joint stress damage evaluation method based on discrete SSI model
Authors: Rong K Y , Zhang S J , Li Y R Y , Wan B 
Published: February 2021

Abstract
Based on the discrete SSI(Stress-strength-interference) model, this paper establishes a stress damage evaluation method for the through-hole insertion process. First, based on the Monte Carlo sampling method, the mean value of solder joint stress was clarified, and a stress-strength interference model for through-hole insertion was established. Secondly, after calculating the shape of the solder joints of the through-holes, the simulated load input curve is determined and the stress simulation is performed to obtain the stress and strain simulation results. The stress and strain of the PCB board are measured through experiments. Finally, a random stress model of solder joints was established by Monte Carlo sampling, and a constant strength model of through-hole solder joints was established in combination with material strength. According to the stress strength interference model, the failure probability of process stress damage was calculated, and the stress damage evaluation of solder joints in through-hole insertion process was realized.
Quantitative analysis of a process industry’s operating status of based on DCS data set
Authors: Chen Qian , Sun Kai 
Published: February 2021

Abstract
The process industry represented by energy chemical enterprise is a typical distributed and complex electromechanical system. Its distributed control system (DCS) records overall operating status information of a process industry. It is a challenge to quantitative operating status through analyzing DCS data set. This paper proposed a novel method to calculate fault score of system’s operating status by classifying its DCS data set and forming a classifier matrix. Firstly, define a classifier matrix depends on the baseline of the DCS data. Secondly, calculate the classifier matrix to obtain the fault score. The higher fault score means the lower security of the system. Last but not least, a period of the system operating status trend could be observed by plotting the fault score. A case study of a real chemical plant is introduced to verify the validation of the method.
Application on the impact domain analysis of on-orbit maintenance in China Space Station
Authors: Lv Zhen , Zhang Hua , Zhao Zhi-Ming , Gong Kai-Xiang 
Published: February 2021

Abstract
On-orbit maintenance is an important means to extend the service life and improve the reliability of the space station. As an essential part of maintainability analysis, impact domain analysis of on-orbit maintenance can find out the deficiency of maintainability design in advance and reduce the risk brought by maintenance. In this paper, the analysis method of the impact domain of the space station on-orbit maintenance is studied, and the working idea of "stage by stage, full coverage, focusing on key points" is put forward to adapt to the development and needs of China Space Station. The process, object, content, and analysis emphasis of the impact domain analysis for different development phases and different kinds of products are determined. The engineering practice shows that reasonable maintenance process and optimal design can be determined by the analysis of the impact area of on-orbit maintenance, which lays the foundation for the good maintainability of China Space Station.
Fatigue test and analysis of Hi-Lock bolt lap joint structure
Authors: Wang L , Li J , Mu H J , Duan L , Lin W Q , Xie L Y 
Published: February 2021

Abstract
Hi-Lock bolt lap joint structure is widely used in aircraft, such as wings, tails and etc. During the service of an aircraft, the joints are subjected to variable loading, which may usually tend to fatigue failure. The single-shear lap joint with four Hi-Lock bolts is taken as the research object. The static tensile test and fatigue test of the Hi-lock bolt lap joint structure are conducted. The macroscopic and microscopic fracture analysis were carried out. It is found that the crack source is located on the joint surface of the two plates, which is on the longitudinal direction away from the edge of the hole, but not on the edge of the connection plate. The results also show that there is no significant difference between the effect of clearance and interference fit on the fatigue life of the lap joint structure under high load conditions.
Research of Multi-objective Component Assignment Problem for Lin/con/k/n System Considering Cost
Authors: Rashid Muhammad , Cao Huiying , Ma Chenyang , Rehman Mudassar , Cai Zhiqiang 
Published: February 2021

AbstractComponent assignment problem (CAP) is widely used in engineering systems, which is investigated for enhancing the system performance by assigning switchable components to several positions. However, the traditional CAP does not consider the cost factor and has limitations for improving the system reliability. Therefore, this paper focus on a multi-objective CAP for Lin/con/k/n system to find the cost-efficient maintenance scheme. Firstly, a multi-objective mathematical optimization model is developed with the aim of maximizing the system reliability and minimizing maintenance cost, which has been proved to be a Non-deterministic polynomial hard problem and should be computed by heuristics. Secondly, a comprehensive maintenance method is adopted to improve the system reliability, which integrates improving the system reliability with changing the permutation of components. To evaluate the contribution of the component reliability on both system reliability and maintenance cost, the multi-objective Birnbaum importance (MOBI) is derived. Finally, MOBI is introduced into the non-dominated sorting genetic algorithm-II (NSGA-II) to solve the optimization model. The numerical experiments for several Lin/con/k/n Systems show that MOBI is available to solve CAP considering cost, and MOBI-based-NSGA-II algorithm is more efficient to obtain higher system reliability with lower maintenance cost.
Fatigue Analysis and Structural Optimization Design of the Slot of Knotted Frame of the Square Baler
Authors: Ma Wei , Cen Hai- tang , Guo Wang , Li Ling , Na Ri-su 
Published: February 2021

Abstract
The frame is a key part to ensure the reliability and life of the knotting device of the square bale baler, and it is also the difficulty of localizing the knotting device. The inner wall of the frame slot of the frame is at a right angle structure, and the stress concentration is obvious. Under the impact load, the stopper will cause premature shear failure, delay the timing of forage bale, increase maintenance costs, and reduce the operating efficiency of the baler. This paper analyzes the failure characteristics of the D-type knotter frame slot, uses ANSYS-nCode joint method to simulate the fatigue life of the knotter frame slot, and uses the response surface method to optimize the design of a U-shaped slot. The simulation results show that when the radius of the U-shaped slot is 2mm and the gap between the bottom of the slot and the first rope clearing piece is 1mm, the fatigue life of the U-shaped slot increases. This research is of reference value to improve the fatigue performance of the knotter frame and enhance the durability of the knotter.
Crack orientation detection in plate-like structures via Lamb wave specular reflection analysis
Authors: Li Xu , Zhang Nan , Zhai Mengsheng 
Published: February 2021

Abstract
The determination of crack orientation plays an important role in the non-destructive evaluation (NDE) of plate-like structures. In this paper, the interaction between Lamb waves and cracks is investigated using the time domain spectral element method (SEM) as the simulation tool. On that basis, we analyse the geometric principle of specular reflections and propose an efficient crack angle detection algorithm. During the process, four sensors take turns to excite the Lamb wave which would result in twelve crack reflection signals. Using the corresponding actuator as the centre and the reflection length as the radius, we can obtain twelve reflection circles in total. When these reflections are specular, the mirror points of the actuators with respect to the crack line are exactly the intersection points of the circles. Thus, we can obtain the crack angle by this geometric relation. Validations on different cracks are made and the result of the algorithm shows a good agreement with the real value.