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Reliability Theory and Applications in Complicated and Smart Systems

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A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Robotics and Automation".

Deadline for manuscript submissions: closed (20 June 2022) | Viewed by 24812

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Prof. Dr. Hong-Zhong Huang

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Guest Editor

Center for System Reliability and Safety, University of Electronic Science and Technology of China, Chengdu 611731, China
Interests: reliability engineering; optimization design; fuzzy sets theory
Special Issues, Collections and Topics in MDPI journals

Prof. Dr. Yan-Feng Li

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Guest Editor

School of Mechanical and Electrical Engineering, University of Electronic Science and Technology of China, Chengdu 611731, China
Interests: system reliability; fuzzy sets theory; uncertainty modeling

Dr. He Li

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Guest Editor

Centre for Marine Technology and Ocean Engineering (CENTEC) Instituto Superior Técnico, Universidade de Lisboa, 1049-001 Lisbon, Portugal
Interests: system reliability; availability; maintainability
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Modern systems and equipment tend to be much more complicated than ever before, facilitated by advancements in new technologies, such as(not limited to) materials and computer sciences, and also by the surge of new technology demand by humans in the most recent years. Systems reliability is a combination of several effective and practical techniques including reliability modeling, reliability analysis, reliability evaluation, reliability prediction, reliability allocation, reliability testing, and so on. It supports the overall performance of systems and equipment as well as the scientific decision-making of stakeholders by analyzing and then avoiding the occurrence of unexpected failures.

This Special Issue is arranged for the collection of original research papers that deal with newly emerged system reliability problems of complicated and smart systems in order to report innovative ideas of system reliability theory or the most recent interesting applications. In collaboration with Applied Sciences (MDPI), up to 20 high-quality papers will be published in this carefully prepared Special Issue after a strict peer-review process. Submissions dealing with the following topics (but not limited to these) are very much welcomed:

System reliability modeling, analysis, evaluation, prediction, allocation, testing;
Maintenance and warranty management;
Quality engineering, availability, and cost issues;
Product reliability and safety (including software reliability);
Fault diagnosis, prognosis, condition monitoring, and PHM;
System analysis, simulation, and optimization;
State-of-the-art applications in complicated and smart systems’ reliability.

Prof. Dr. Hong-Zhong Huang
Prof. Dr. Yan-Feng Li
Dr. He Li
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Applied Sciences is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

quality and reliability engineering
reliability theory and application
reliability testing and statistics
risk management
prognostics and health management
equipment management and maintenance
optimal design
applications of complicated/smart products

Published Papers (12 papers)

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Research

14 pages, 3889 KiB

Open AccessArticle

Abnormal Conductive State Identification of the Copper Rod in a Nickel Electrolysis Procedure Based on Infrared Image Features and Position Characteristics

by Rui Sun, Gang Qin, Gaibian Li, Jinbao Hu, Jingqi Xiong and Huanwei Xu

Appl. Sci. 2022, 12(7), 3691; https://0-doi-org.brum.beds.ac.uk/10.3390/app12073691 - 06 Apr 2022

Cited by 2 | Viewed by 1595

Abstract

In the nickel electrolysis industry, detection of the conductive state of copper rods is an important part of production procedure management, as abnormal conductive states of the copper rod result in a decline in the quality of the electrodeposited nickel plate. Conventional treatment consists of manual detection and handing, which is inefficient and induces more problems, such as the safety of the insulation. Because abnormal conductive states are only located between the copper rod and busbar, it has obvious position characteristics, and abnormal conductive states also induce a calorific difference in a particular area, which can be detected in an infrared image. We can use the infrared feature and position characteristics to identify the abnormal conductive faults. This paper introduces a method and practice for the identification of abnormal conductive faults in a conductive copper rod in the nickel electrolysis procedure using computer vision theory, including infrared image segmentation with position characteristics, infrared feature extraction, and conductive fault identification with SVM (support vector machine). The result shows that the method can divide the conductive states of the copper rod into abnormal heating conditions, normal operating conditions, and open circuit conditions, with a 90% accuracy rate on the obtained samples. Full article

(This article belongs to the Special Issue Reliability Theory and Applications in Complicated and Smart Systems)

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14 pages, 11780 KiB

Open AccessArticle

In-Orbit Reliability Evaluation of Space TWTA Based on Copula Function and Bivariate Hybrid Stochastic Processes

by Xiao-Ning Wang, Xiao-Bao Su, Dong-Dong Ma, Rui Zhang, Guo-Xing Miao and Wei-Long Wang

Appl. Sci. 2022, 12(3), 1575; https://0-doi-org.brum.beds.ac.uk/10.3390/app12031575 - 01 Feb 2022

Cited by 3 | Viewed by 1591

Abstract

Currently, it is still a challenge to study the degradation mechanisms of the space traveling wave tube amplifier (TWTA) with no failure and small sample tests. Given that the Copula functions are used to describe the correlation of multiple performance characteristics, this paper develops a bivariate hybrid stochastic degradation model to evaluate the in-orbit reliability of TWTA. Firstly, based on the impact analysis of the life of TWTA, helix current and anode voltage are selected as the performance degradation parameters. Secondly, stochastic processes with random effects based on the one-dimensional Wiener process and Gamma process are applied to describe the degradation of TWTA’s helix current and anode voltage, respectively, and the corresponding marginal distribution function is obtained. Then, the Copula function is utilized to describe the correlation between two different performance parameters of TWTA. Meanwhile, this paper also proposed a two-step method to estimate the reliability level of TWTA based on its in-orbit telemetry data through a two-step method, which contains a Markov Chain Monte Carlo (MCMC) algorithm and a maximum likelihood estimation (MLE) algorithm. Besides, the Bayes-Bootstrap sampling method is also used to improve the evaluation accuracy to overcome the defect of an in-orbit small sample of TWTA. Finally, a TWTA degradation case with a set of telemetry data is carried out, and the results show that the method proposed in this paper is more applicable and more accurate than other methods. Full article

(This article belongs to the Special Issue Reliability Theory and Applications in Complicated and Smart Systems)

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10 pages, 4217 KiB

Open AccessArticle

Experimental Investigation of Clearance Influences on Cage Motion and Wear in Ball Bearings

by Baogang Wen, Meiling Wang, Xu Zhang, Jingyu Zhai and Wei Sun

Appl. Sci. 2021, 11(24), 11848; https://0-doi-org.brum.beds.ac.uk/10.3390/app112411848 - 13 Dec 2021

Cited by 5 | Viewed by 2357

Abstract

Clearances of cages in ball bearings, including pocket and guiding clearances, play a vital role in the stability and reliability of bearings. In this paper, experiments on the cage motion and wear were carried out to investigate the influence of clearances in ball bearings. Firstly, the cages with a series of pocket and guiding clearances were specially designed and tested for prescribed operating conditions on a bearing test rig in which the cage motions were measured, and corresponding wear was also observed. Then, the normalized trajectory, waveform, and spectra of cage motion were constructed and compared to illustrate the effects of clearances on the cage motion and then to establish the relationship between cage motion and wear. Results reveal that the cage motion and wear are both significantly affected by its clearances. The increment of cage guiding clearance makes the whirl trajectories of the cage regular and the motion frequency of cage motion significantly change. However, the increment of cage pocket clearance make the whirl trajectories change from well-defined patterns to complicated ones, and the frequency of cage motion apparently changes. Additionally, the bearing wear is closely related to the cage motion. If the inner ring frequency is of domination for the cage motion, the cage guiding surface will wear seriously. While cage motion is dominated by two times cage frequency in spectrum domain, the cage pocket will wear more seriously. Full article

(This article belongs to the Special Issue Reliability Theory and Applications in Complicated and Smart Systems)

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11 pages, 1107 KiB

Open AccessArticle

Reliability Modeling and Analysis of Multi-Degradation of Momentum Wheel Based on Copula Function

by Yan-Feng Li, Ming Huang, Song Bai, Yuan Chen and Hong-Zhong Huang

Appl. Sci. 2021, 11(23), 11563; https://0-doi-org.brum.beds.ac.uk/10.3390/app112311563 - 06 Dec 2021

Cited by 2 | Viewed by 1673

Abstract

The momentum wheel is a key component of the satellite attitude control system and has a direct impact on the reliability and overall life of the satellite. The momentum wheel has the characteristics of a high reliability, long life, and complex failure mechanics, which leads to expensive maintenance and a low reliability of the test sample. Therefore, it is challenge to implement an accelerated life test. The traditional life data statistical method has great difficulty in solving the reliability analysis of the momentum wheel. A reliability calculation method based on copula function for multi-degradation is proposed. Firstly, the key factors affecting the reliability of the momentum wheel are analyzed, and the lubricant residual quantity and current are selected as the degradation quantity. Secondly, the wiener process is used to model the degradation of a single degradation quantity, and the edge distribution function of the momentum wheel reliability is obtained. Considering that the correlation between multiple degradation quantities has a non-negligible influence on the reliability analysis result, the copula function is introduced to describe the correlation, and the edge distributions are fused to obtain the joint distribution function of the momentum wheel reliability. Full article

(This article belongs to the Special Issue Reliability Theory and Applications in Complicated and Smart Systems)

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14 pages, 38448 KiB

Open AccessArticle

Effects of Environmental and Electrical Factors on Metering Error and Consistency of Smart Electricity Meters

by Suqin Xiong, Jiahai Zhang, Baoliang Zhang, Guodong Sun, Zhen Chen, Jia Qi and Yongquan Sun

Appl. Sci. 2021, 11(23), 11457; https://0-doi-org.brum.beds.ac.uk/10.3390/app112311457 - 03 Dec 2021

Cited by 1 | Viewed by 2494

Abstract

The smart electricity meter (SEM) is an important part of smart power grid, and the accuracy of SEMs is the basis for power grid operation control and trade settlement between power supply and electricity consumption, but the evolution behaviors of metering error of SEMs under field operation conditions have not yet been identified. The SEMs were installed and operated on site, metering error data were collected under various temperature and current conditions. The influences of current, power coefficient, and temperature on metering error and consistency were analyzed separately with the help of quadratic polynomials, and then an integrated model elaborating the joint effects of multi-stress was developed based on a binary quadratic polynomial. We find that a lower temperature and a larger current result in a higher metering error of SEMs; however, the effects of current on metering error are determined by power coefficients. The results have reference value for remote metrological verification, error monitoring, and the optimization of the operation and maintenance scheme of SEMs. Full article

(This article belongs to the Special Issue Reliability Theory and Applications in Complicated and Smart Systems)

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14 pages, 5625 KiB

Open AccessArticle

Reliability Analysis of CFRP-Packaged FBG Sensors Using FMEA and FTA Techniques

by Zheng Liu, Yongjie Li, Nan Zhang, Zhongwei Liang and Fangyi Li

Appl. Sci. 2021, 11(22), 10859; https://0-doi-org.brum.beds.ac.uk/10.3390/app112210859 - 17 Nov 2021

Cited by 3 | Viewed by 1577

Abstract

Carbon fiber-reinforced plastics (CFRP)-packaged fiber Bragg grating (FBG) sensors are widely used in full-scale structural testing of wind turbine blades (WTBs). However, the specific process to make CFRP-packaged FBG sensors, such as packaging, bonding, welding, etc., are mainly manually operated, and no unified standard or rule has been formed yet. Non-standard specific processes, coupled with complex stress distribution, unstable working environments, etc., result in the CFRP-packaged FBG sensors having various failures with time, resulting in inaccurate measurements. Thus, the need to carry out related failure analysis is urgent. This paper therefore performed a reliability analysis for CFRP-packaged FBG sensors using failure mode and effects analysis (FMEA) and fault tree analysis (FTA) techniques. The results provide an important basis towards analyzing performance degradation and functional failures for CFRP-packaged FBG sensors. Full article

(This article belongs to the Special Issue Reliability Theory and Applications in Complicated and Smart Systems)

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10 pages, 2860 KiB

Open AccessArticle

Intelligent Prediction of Aeroengine Wear Based on the SVR Optimized by GMPSO

by Bo Zheng, Feng Gao, Xin Ma and Xiaoqiang Zhang

Appl. Sci. 2021, 11(22), 10592; https://0-doi-org.brum.beds.ac.uk/10.3390/app112210592 - 10 Nov 2021

Cited by 3 | Viewed by 1125

Abstract

In order to predict aeroengine wear accurately and automatically, as a predictor, support vector regression (SVR) was optimized by means of particle swarm optimization (PSO). The guided mutation strategy of PSO (GMPSO) is presented herein to determine the proper structure parameters of an SVR, as well as the embedding dimensions of the training samples. The guided mutation strategy was able to increase the diversity of particles and improve the probability of finding the global extremum. Furthermore, single-step and multi-step prediction methods were designed to meet different accuracy requirements. A prediction comparison study on spectral analysis data was carried out, and the contrast experiments show that compared with SVR optimized by means of a traditional PSO, a neural network and an auto regressive moving average (ARMA) prediction model, the SVR optimized by means of the GMPSO approach produced prediction results not only with higher accuracy, but also with better consistency. Full article

(This article belongs to the Special Issue Reliability Theory and Applications in Complicated and Smart Systems)

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11 pages, 1960 KiB

Open AccessArticle

Reliability Assessment of Space Station Based on Multi-Layer and Multi-Type Risks

by Xiaopeng Li and Fuqiu Li

Appl. Sci. 2021, 11(21), 10258; https://0-doi-org.brum.beds.ac.uk/10.3390/app112110258 - 01 Nov 2021

Cited by 2 | Viewed by 1281

Abstract

A space station is a typical phased-mission system, and assessing its reliability during its configuration is an important engineering action. Traditional methods usually require extensive data to carry out a layered reliability assessment from components to the system. These methods suffer from lack of sufficient test data, and the assessment process becomes very difficult, especially in the early stage of the configuration. This paper proposes a reliability assessment method for the space station configuration mission, using multi-layer and multi-type risks. Firstly, the risk layer and the risk type for the space station configuration are defined and identified. Then, the key configuration risks are identified comprehensively, considering their occurrence likelihood and consequence severity. High load risks are identified through risk propagation feature analysis. Finally, the configuration reliability model is built and the state probabilities are computed, based on the probabilistic risk propagation assessment (PRPA) method using the assessment probability data. Two issues are addressed in this paper: (1) how to build the configuration reliability model with three layers and four types of risks in the early stage of the configuration; (2) how to quantitatively assess the configuration mission reliability using data from the existing operational database and data describing the propagation features. The proposed method could be a useful tool for the complex aerospace system reliability assessment in the early stage. Full article

(This article belongs to the Special Issue Reliability Theory and Applications in Complicated and Smart Systems)

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17 pages, 2408 KiB

Open AccessArticle

A Novel Method for Detecting Advanced Persistent Threat Attack Based on Belief Rule Base

by Guozhu Wang, Yiwen Cui, Jie Wang, Lihua Wu and Guanyu Hu

Appl. Sci. 2021, 11(21), 9899; https://0-doi-org.brum.beds.ac.uk/10.3390/app11219899 - 22 Oct 2021

Cited by 8 | Viewed by 2164

Abstract

Advanced persistent threat (APT) is a special attack method, which is usually initiated by hacker groups to steal data or destroy systems for large enterprises and even countries. APT has a long-term and multi-stage characteristic, which makes it difficult for traditional detection methods to effectively identify. To detect APT attacks requires solving some problems: how to deal with various uncertain information during APT attack detection, how to fully train the APT detection model with small attack samples, and how to obtain the interpretable detection results for subsequent APT attack forensics. Traditional detection methods cannot effectively utilize multiple uncertain information with small samples. Meanwhile, most detection models are black box and lack a transparent calculation process, which makes it impossible for managers to analyze the reliability and evidence of the results. To solve these problems, a novel detection method based on belief rule base (BRB) is proposed in this paper, where expert knowledge and small samples are both utilized to obtain interpretable detection results. A case study with numerical simulation is established to prove the effectiveness and practicality of the proposed method. Full article

(This article belongs to the Special Issue Reliability Theory and Applications in Complicated and Smart Systems)

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11 pages, 8921 KiB

Open AccessArticle

Open Localization in 3D Package with TSV Daisy Chain Using Magnetic Field Imaging and High-Resolution Three-Dimensional X-ray Microscopy

by Yuan Chen, Ping Lai, Hong-Zhong Huang, Peng Zhang and Xiaoling Lin

Appl. Sci. 2021, 11(17), 8148; https://0-doi-org.brum.beds.ac.uk/10.3390/app11178148 - 02 Sep 2021

Cited by 2 | Viewed by 1993

Abstract

With the development of 3D integrated packaging technology, failure analysis is facing more and more challenges. Defect localization in a 3D package is a key step of failure analysis. The complex structure and materials of 3D package devices demand non-destructive defect localization technology for full packages. Magnetic field imaging and three-dimensional X-ray technology are not affected by package material or form. They are effective methods to realize defect localization on 3D packages. In this paper, magnetic field imaging and high-resolution three-dimensional X-ray microscopy were used to localize the open defect in a 3D package with a TSV daisy chain. A two-probe RF method in magnetic field imaging was performed to resolve isolation of the defect difficulties resulting from many different branches of TSV daisy chains. Additionally, a linear decay method was used to target sub-micron resolution at a long working distance. Multiple partition scans from a high-resolution 3D X-ray microscopy with a two-stage magnification structure were used to achieve sub-micron resolution. The open location identified by magnetic field imaging was consistent with that identified by a three-dimensional X-ray microscope. The opening was located on the top metal in the proximity of the fifth via. Physical failure analysis revealed the presence of a crack in the top metal at the opening location. Full article

(This article belongs to the Special Issue Reliability Theory and Applications in Complicated and Smart Systems)

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15 pages, 23803 KiB

Open AccessArticle

Fault Detection for Pitch System of Wind Turbine-Driven Doubly Fed Based on IHHO-LightGBM

by Mingzhu Tang, Zhonghui Peng and Huawei Wu

Appl. Sci. 2021, 11(17), 8030; https://0-doi-org.brum.beds.ac.uk/10.3390/app11178030 - 30 Aug 2021

Cited by 6 | Viewed by 1603

Abstract

To address the issue of a large calculation and difficult optimization for the traditional fault detection of a wind turbine-based pitch control system, a fault detection model, based on LightGBM by the improved Harris Hawks optimization algorithm (light gradient boosting machine by the improved Harris Hawks optimization, IHHO-LightGBM) for the wind turbine-based pitch control system, is proposed in this article. Firstly, a trigonometric function model is introduced by IHHO to update the prey escape energy, to balance the global exploration ability and local development ability of the algorithm. In this model, the fault detection false alarm rate is used as the fitness function, and the two parameters are used as the optimization objects of the improved Harris Hawks optimization algorithm, to optimize the parameters, so as to achieve the global optimal parameters to improve the performance of the fault detection model. Three different fault data of the pitch control system in actual operations of domestic wind farms are used as the experimental data, the Pearson correlation analysis method is introduced, and the wind turbine power output is taken as the main state parameter, to analyze the correlation degree of all the characteristic variables of the data and screen the important characteristic variables out, so as to achieve the effective dimensionality reduction process of the data, by using the feature selection method. Three established fault detection models are selected and compared with the proposed method, to verify its feasibility. The experimental data indicate that compared with other algorithms, the fault detecting ability of the proposed model is improved in all aspects, and the false alarm rate and false negative rate are lower. Full article

(This article belongs to the Special Issue Reliability Theory and Applications in Complicated and Smart Systems)

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15 pages, 2237 KiB

Open AccessArticle

Joint Optimization Method of Spare Parts Stocks and Level of Repair Analysis Considering the Multiple Failure Modes

by Ruiqi Wang, Guangyu Chen, Jie Wu, Wei Zhou and Zheng Huang

Appl. Sci. 2021, 11(16), 7254; https://0-doi-org.brum.beds.ac.uk/10.3390/app11167254 - 06 Aug 2021

Cited by 3 | Viewed by 1714

Abstract

For the repair level and spare parts stocking problems, generally METRIC type methods and Level of repair analysis (LORA) are used separately. Since LORA does not consider the availability of capital goods, solving LORA and spare parts stocking problems sequentially may lead to suboptimal solutions. On these considerations, this study presents a joint optimization method to minimize the service logistics cost under the constraints of system availability. Maintenance capability factor and maintenance decisions are introduced into the joint optimization model to express the influence of multiple failure modes on repair level and spare parts stocking. Thus, we establish the bridge relationship between LORA and METRIC models. The joint optimization model is solved by an improved iterative algorithm, and a typical fleet system is taken as an example to verify the correctness and effectiveness of the model and the algorithm. Compared with the optimization of spare parts inventory and maintenance level independently, the joint optimization method could effectively reduce the service logistic system cost. Full article

(This article belongs to the Special Issue Reliability Theory and Applications in Complicated and Smart Systems)

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