Bayesian Reliability Assessment Method for Single NC Machine Tool Under Zero Failures

Li, Hongzhou; Chen, Fei; Yang, Zhaojun; Kan, Yingnan; Wang, Liding

doi:10.1007/978-3-662-48683-2_26

Cited by 4 publications

(7 citation statements)

References 12 publications

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“…e latter is obtained from the performance degradation information of the equipment, and it reflects the real time reliability of the equipment [2]. In engineering field, single or small batch equipment is widely used, and failure data are very scarce in this case, so the traditional statistical method is not suitable for the reliability evaluation of this type of mechanical equipment, such as high precision NC machine tools, nuclear power facilities, aircraft [3][4][5], and so on. In contrast, the operational reliability is more of practical significance to ensure the safety of this type of equipment because it can be obtained in real time when the condition monitoring data are sampled continuously.…”

Section: Introductionmentioning

confidence: 99%

Equipment Operational Reliability Evaluation Method Based on RVM and PCA-Fused Features

Zhu

Dong

Feng

2021

Mathematical Problems in Engineering

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Reliability assessment is of great significance in ensuring the safety and reducing maintenance cost of equipment. The traditional statistical method is widely used to estimate the reliability of mass equipment; however, it cannot efficiently predict the overall reliability of single or small batch equipment due to lack of failure data. This paper introduced the operational reliability concept to describe the running condition of single or small batch equipment and proposed a method based on the combination of Relevance Vector Machines (RVMs) and Principal Component Analysis (PCA) to evaluate the operational reliability. Some representative characteristic indexes of operating equipment were firstly selected, and PCA was applied to obtain a hybrid index of the equipment’s running condition. Then, a RVM prediction model was trained to predict the development of the hybrid index and corresponding probability density function (PDF). Based on this, the operational reliability of the equipment was calculated by the interval integral defined by the failure threshold and the predicted value of the hybrid index. The approach was validated using the experimental test conducted on the aero-engine rotor bearings. The results show a good agreement in the evaluations of the failure time between the proposed method and the experimental test.

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Section: Introductionmentioning

confidence: 99%

Equipment Operational Reliability Evaluation Method Based on RVM and PCA-Fused Features

Zhu

Dong

Feng

2021

Mathematical Problems in Engineering

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“…e Bayesian method is an effective method to deal with the reliability problem of products with few failure information. It has been widely used in reliability parameter point estimation [1,2]. Martz and Waller [3] studied the reliability evaluation problem under the condition of no failure data for the first time.…”

Section: Introductionmentioning

confidence: 99%

Reliability Assessment for Very Few Failure Data and Weibull Distribution

Zhang

Jin

You

2019

Mathematical Problems in Engineering

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Only very few failure data can be obtained for the time censored test of high-reliability and long-life products. For very few failure data, the current methods fail to obtain both the point estimation and confidence interval of reliability parameters. If the point estimation and confidence interval of reliability parameters are obtained based on different methods, the results tend to be unreliable. In this study, based on the existing research, a Bayesian reliability evaluation method for very few failure data under the Weibull distribution was proposed. First, the range of failure probability was limited based on the convexity and self-features of the Weibull distribution function. Second, based on the background of the sample with very few failure data, the pretest distribution function and parameters were set and solved. The point estimation and confidence interval model of failure probability based on the Bayesian formula was established. The improved match distribution curve method was used to compute both the point estimation and confidence interval of reliability parameters. Furthermore, by comparing the results of numerical examples, the calculation results obtained by the proposed method were verified as being very reasonable. Finally, taking wet friction plates as an example, the results showed the effectiveness of this method in engineering practice.

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“…e precision of estimation results of reliability increased significantly based on the hierarchical Bayesian estimation. Li et al [17] built a Bayes model of the zero-failure problem for a single NC machine tool and presented the method of building the prior distributions of Weibull parameters. e method can be said to be a standard solution to the zero-failure reliability assessment for NC machine tools.…”

Section: Introductionmentioning

confidence: 99%

Vibration Reliability Evaluation of Main Fan Spindle Bearings

Pang

Qiu

Liang

et al. 2019

Shock and Vibration

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Based on an analysis of failure causes, the axial force is the main reason why spindle bearings vibrate abnormally and cause frequent failures of the main fans in mines. In this paper, the probability density function of the spindle bearing vibration was established through the bootstrap maximum entropy method, the Lagrangian multiplier and the empirical coefficient were introduced, and models of the upper- and lower-bound functions of the probability density and the true value function of the failure probability were established. The true value function and interval estimation values of vibration reliability were obtained on the basis of maximum entropy. The analysis results showed that the estimation true values of vibration decreased with an increase in the empirical coefficient. When the empirical coefficient was less than 0.1, the estimated true value decreased sharply. When the empirical coefficient was greater than 0.1, the vibration value decreased linearly with the empirical coefficient. When the empirical coefficient was 0.1, the estimated true value was 0.85 mm/s2, which is consistent with the change in the actual vibration value. Therefore, when the main fan is fault predicted, the vibration value should be 0.85 mm/s2 as the basis for judgment and then the theoretical basis for the fault diagnosis of the spindle bearing are provided.

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Bayesian Reliability Assessment Method for Single NC Machine Tool Under Zero Failures

Cited by 4 publications

References 12 publications

Equipment Operational Reliability Evaluation Method Based on RVM and PCA-Fused Features

Equipment Operational Reliability Evaluation Method Based on RVM and PCA-Fused Features

Reliability Assessment for Very Few Failure Data and Weibull Distribution

Vibration Reliability Evaluation of Main Fan Spindle Bearings

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