The Experts below are selected from a list of 60252 Experts worldwide ranked by ideXlab platform
Tadashi Dohi - One of the best experts on this subject based on the ideXlab platform.
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ISSRE - On the Effect of Fault Removal in Software Testing - Bayesian Reliability Estimation Approach
2006 17th International Symposium on Software Reliability Engineering, 2006Co-Authors: H. Okamura, H. Furumura, Tadashi DohiAbstract:In this paper, we propose some Reliability Estimation methods in software testing. The proposed methods are based on the familiar Bayesian statistics, and can be characterized by using test outcomes in input domain models. It is shown that the resulting approaches are capable of estimating software Reliability in the case where the detected software faults are removed. In numerical examples, we compare the proposed methods with the existing method, and investigate the effect of fault removal on the Reliability Estimation in software testing. We show that the proposed methods can give more accurate estimates of software Reliability
Gaigai Cai - One of the best experts on this subject based on the ideXlab platform.
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Reliability Estimation for cutting tools based on logistic regression model using vibration signals
Mechanical Systems and Signal Processing, 2011Co-Authors: Baojia Chen, Xuefeng Chen, Hongrui Cao, Gaigai CaiAbstract:As an important part of CNC machine, the Reliability of cutting tools influences the whole manufacturing effectiveness and stability of equipment. The present study proposes a novel Reliability Estimation approach to the cutting tools based on logistic regression model by using vibration signals. The operation condition information of the CNC machine is incorporated into Reliability analysis to reflect the product time-varying characteristics. The proposed approach is superior to other degradation Estimation methods in that it does not necessitate any assumption about degradation paths and probability density functions of condition parameters. The three steps of new Reliability Estimation approach for cutting tools are as follows. First, on-line vibration signals of cutting tools are measured during the manufacturing process. Second, wavelet packet (WP) transform is employed to decompose the original signals and correlation analysis is employed to find out the feature frequency bands which indicate tool wear. Third, correlation analysis is also used to select the salient feature parameters which are composed of feature band energy, energy entropy and time-domain features. Finally, Reliability Estimation is carried out based on logistic regression model. The approach has been validated on a NC lathe. Under different failure threshold, the Reliability and failure time of the cutting tools are all estimated accurately. The positive results show the plausibility and effectiveness of the proposed approach, which can facilitate machine performance and Reliability Estimation.
H. Okamura - One of the best experts on this subject based on the ideXlab platform.
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ISSRE - On the Effect of Fault Removal in Software Testing - Bayesian Reliability Estimation Approach
2006 17th International Symposium on Software Reliability Engineering, 2006Co-Authors: H. Okamura, H. Furumura, Tadashi DohiAbstract:In this paper, we propose some Reliability Estimation methods in software testing. The proposed methods are based on the familiar Bayesian statistics, and can be characterized by using test outcomes in input domain models. It is shown that the resulting approaches are capable of estimating software Reliability in the case where the detected software faults are removed. In numerical examples, we compare the proposed methods with the existing method, and investigate the effect of fault removal on the Reliability Estimation in software testing. We show that the proposed methods can give more accurate estimates of software Reliability
Shaoping Wang - One of the best experts on this subject based on the ideXlab platform.
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Reliability Estimation from lifetime testing data and degradation testing data with measurement error based on evidential variable and Wiener process
Reliability Engineering & System Safety, 2021Co-Authors: Di Liu, Shaoping WangAbstract:Abstract Evidential variable has been applied in Wiener process based Reliability Estimation due to its powerful ability on parameter describing. The previously published evidential variable and stochastic process based Reliability Estimation methods neglect measurement error and cannot utilize lifetime testing data. However, in practical applications, lifetime testing is an important approach and measurement error is an inevitable factor. Hence, in this paper, the evidential variable and Wiener process based Reliability Estimation method is improved to handle the above issues. A simulation study is used to verify the effectiveness of the proposed Reliability Estimation method. Furthermore, an actual engineering case on piston pump is also studied to demonstrate the proposed method in engineering practice. It is concluded that utilizing lifetime testing data and considering measurement error can improve the accuracies of model parameter evaluation, degradation prediction, Reliability Estimation and etc., in evidential and Wiener process based Reliability Estimation.
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Reliability Estimation of Reciprocating Seals Based on Multivariate Dependence Analysis and Its Experimental Validation
IEEE Access, 2019Co-Authors: Chao Zhang, Shaoping Wang, Rentong Chen, Yujie Qian, Mileta M. TomovicAbstract:Accurate Reliability Estimation for reciprocating seals is of great significance due to their wide use in numerous engineering applications. This work proposes a Reliability Estimation method for reciprocating seals based on multivariate dependence analysis of different performance indicators. Degradation behavior corresponding to each performance indicator is first described by the Wiener process. Dependence among different performance indicators is then captured using D-vine copula, and a weight-based copula selection method is utilized to determine the optimal bivariate copula for each dependence relationship. A two-stage Bayesian method is used to estimate the parameters in the proposed model. Finally, a reciprocating seal degradation test is conducted, and the proposed Reliability Estimation approach is validated by test data. Results show that the proposed model is accurate and effective in estimating the Reliability of reciprocating seals.
Xiaozong Yang - One of the best experts on this subject based on the ideXlab platform.
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SA based software deployment Reliability Estimation considering component dependence
Journal of Electronics (China), 2011Co-Authors: Hongwei Liu, Xiaozong Yang, Decheng ZuoAbstract:Reliability is one of the most critical properties of software system. System deployment architecture is the allocation of system software components on host nodes. Software Architecture (SA) based software deployment models help to analyze Reliability of different deployments. Though many approaches for architecture-based Reliability Estimation exist, little work has incorporated the influence of system deployment and hardware resources into Reliability Estimation. There are many factors influencing system deployment. By translating the multi-dimension factors into degree matrix of component dependence, we provide the definition of component dependence and propose a method of calculating system Reliability of deployments. Additionally, the parameters that influence the optimal deployment may change during system execution. The existing software deployment architecture may be ill-suited for the given environment, and the system needs to be redeployed to improve Reliability. An approximate algorithm, A*_D, to increase system Reliability is presented. When the number of components and host nodes is relative large, experimental results show that this algorithm can obtain better deployment than stochastic and greedy algorithms.
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A Comprehensive Approach of SA Based Software Deployment Reliability Estimation in Neural Networks
2010 First International Conference on Pervasive Computing Signal Processing and Applications, 2010Co-Authors: Hongwei Liu, Decheng Zuo, Xiaozong YangAbstract:Software architecture (SA) has been widely advocated as an effective abstraction for modeling, implementing, and evolving complex software systems such as those in distributed, decentralized, heterogeneous and pervasive environments. We intend to investigate two problems related to the domain of those environments: software deployment and Reliability. Though many approaches for Architecture-based Reliability research, little work has been done in incorporating software deployment into SA based Reliability Estimation. This paper presents a new comprehensive approach of Reliability Estimation considering software deployment in neural networks. Additionally, we explain software component replica and different software component deployment architectures in neural networks.
