Estimation of Tire Wear and Traumatic Event Intensities

2002 ◽  
Vol 30 (4) ◽  
pp. 214-239 ◽  
Author(s):  
V. Bagdonavičius ◽  
A. Bikelis ◽  
V. Kazakevicius
Keyword(s):  
Failure Modes ◽  
Failure Time ◽  
Traumatic Event ◽  
Survival Function ◽  
Wear Model ◽  
Probability Of Survival ◽  
Degradation Data ◽  
Reliability Characteristics ◽  
Tire Wear ◽  
The Mean

Abstract A tire wear model including dependence of the distribution of the traumatic failures of various modes on the wear is proposed. Non-parametric, semi-parametric and parametric methods of estimation for the main reliability characteristics of tires are given. The model makes it possible not only to estimate unconditional functions such as the survival function and the mean failure time of tires and the probabilities of failures of the particular modes, but also to predict residual characteristics such as the probability of survival given the run and the wear of a tire, to estimate the ideal reliability characteristics and to predict reliability of tires when causes of the particular traumatic failure modes are eliminated. Analysis of the real failure time and degradation data of tires is given.

Semiparametric Estimates and Goodness-of-Fit Tests for Tire Wear and Failure Time Data

2002 ◽  
Vol 7 (1) ◽  
pp. 61-95 ◽  
Author(s):  
Rūta Levulienė
Keyword(s):  
Goodness Of Fit ◽  
Failure Modes ◽  
Failure Time ◽  
Traumatic Event ◽  
Failure Time Data ◽  
Time Data ◽  
Goodness Of Fit Test ◽  
Goodness Of Fit Tests ◽  
Reliability Characteristics ◽  
Tire Wear

The goodness-of-fit test for tire wear and failure time data with multiple failure modes is proposed. Parametric estimators of traumatic event cumulative intensities and semiparametric estimates of various reliability characteristics are given and their large sample properties are investigated.  Real tire wear and failure time data are analyzed.

Research on Compilation Method of Multi-Axial Loading Spectrum for Cylindrical Shock Absorber

2017 ◽  
Vol 24 (05) ◽  
pp. 1750023 ◽  
Author(s):  
Qi Gao ◽  
Jinzhi Feng ◽  
Songlin Zheng ◽  
Xuyun Qiu
Keyword(s):  
Failure Mode ◽  
Failure Modes ◽  
Failure Time ◽  
Axial Loading ◽  
Bench Test ◽  
Cylinder Wall ◽  
Vertical Loading ◽  
Field Samples ◽  
The Mean ◽  
Loading Spectrum

The main failure mode of cylindrical shock absorbers (CSAs) used by taxis in China’s Zhejiang Province is oil leakage because of a large horizontal force loaded on the cylinder wall by a questionnaire survey. The previous CSA durability bench test methods, which do not involve the interaction between horizontal load and vertical load and do not consider the user road spectrum, cannot simulate the real fatigue phenomena of it. In order to preferably reproduce the failure mode and accurately to predict the failure time of the CSA used in the area, a compilation method of multi-axial loading spectrum is proposed based on the road spectrum. The vertical loading spectrum is compiled by using the way of sine on sine, in which high frequency (HF) signal superimposed on low frequency (LF) signal. The LF is determined by the half-power bandwidth theory, which can reflect the power spectral density distribution of the random road spectrum. The HF is determined by the maximum line velocity principle to effectively reduce test time. The loading cycles and amplitudes of them are determined by using the rain-flow counting method. In addition, the horizontal loading force is taken into consideration in the multi-axial loading spectrum. To prove the validation and efficiency of the method described in this paper, the compiled multi-axial loading spectrum was used to conduct the durability bench test. The results show that the mean failure mileage of specimens is close to the mean mileage time of field samples. The failure modes of the specimens are the same as those of field samples. Thus the proposed method can be used as a reference for durability bench test of CSA. The test data can also be used to accurately study the reliability of CSA.

EVALUATION OF THE RELIABILITY OF COMPLEX TECHNICAL RECONFIGURATION SYSTEMS BY STATISTICAL MODELING METHOD

2019 ◽  
pp. 84-88
Author(s):  
A.Yu. Kulakov
Keyword(s):  
Normal Distribution ◽  
Statistical Modeling ◽  
Quantitative Estimate ◽  
Failure Time ◽  
Modeling Method ◽  
System Failure ◽  
Similar System ◽  
Orbit Control ◽  
Reliability Characteristics ◽  
Complex Technical System

Goal. Assess the reliability of a complex technical system with periodic reconfiguration and compare the results obtained a similar system, but without reconfiguration. Materials and methods. In this article uses the method of statistical modeling (Monte Carlo) to assess the reliability of complex system. We using the normal and exponential distribution of failure time for modeling failures of system elements. Reconfiguration algorithm is the algorithm proposed for the attitude and orbit control system of spacecraft. Results. A computer program has been developed for assessing reliability on the basis of a statistical modeling method, which makes it possible to evaluate systems of varying complexity with exponential and normal distribution, as well as with and without periodic reconfiguration. A quantitative estimate of the reliability as a function of the probability of system failure is obtained. Conclusion. It has been demonstrated that a system with reconfiguration has the best reliability characteristics, both in the case of exponential and normal distribution of failures.

Abstract P606: Hemodynamic Predictors of Multiple Recurrent Strokes in the Patients With Prior Lacunar Stroke

Stroke ◽  
2021 ◽  
Vol 52 (Suppl_1) ◽  
Author(s):  
Adam H de Havenon ◽  
Alexandra Kvernland ◽  
Alen Delic ◽  
Ka-ho Wong ◽  
Nazanin Sheibani ◽  
...  
Keyword(s):  
Blood Pressure ◽  
Logistic Regression ◽  
Failure Time ◽  
Recurrent Stroke ◽  
Cox Proportional Hazards Model ◽  
Lacunar Stroke ◽  
Blood Pressures ◽  
Recurrent Strokes ◽  
The Mean

Background: Recurrent stroke has higher morbidity and mortality than incident stroke. We evaluated hemodynamic risk factors for multiple recurrent strokes. Methods: We included patients in the SPS3 trial. The primary predictor was the top tertile, compared to the bottom tertile, of the mean systolic blood pressure (mSBP) and blood pressure variability represented as standard deviation (sdSBP) using blood pressures from day 30 of the trial to the end of follow-up. We excluded blood pressures from the first 30 days to reduce confounding from the trial’s intervention. We fit a logistic regression model to ≥2 recurrent strokes from day 30 to the end of follow-up and, to accurately analyze the multiple failure-time data, we ordered the multiple failure events to the Prentice, Williams and Peterson extension of the Cox proportional-hazards model. Results: We included 2,882 patients, of which 223 had a recurrent stroke and 41/223 had ≥2 recurrent strokes for a total of 272 strokes. The mean (SD) number of blood pressure readings was 78.0 (37.4). The etiology of the 272 strokes was 161 (59.2%) lacunar, 22 (8.1%) intracranial atherosclerosis, 10 (3.7%) extracranial atherosclerosis, 24 (8.8%) cardioembolic, and 55 (20.2%) cryptogenic or other. In both unadjusted and adjusted logistic regression models and PWP Cox models, the top tertile of sdSBP was consistently predictive of multiple recurrent strokes, while mSBP was not (Tables 1/2). Conclusions: We found that in patients with an index lacunar stroke, higher SBP variability, but not mean SBP, was predictive of multiple recurrent strokes of varying mechanisms.

Bayesian Nonparametric Estimation of Failure Rates with Censored Data

1983 ◽  
Vol 32 (1-2) ◽  
pp. 79-90 ◽  
Author(s):  
J. S. Rao ◽  
R. C. Tiwari
Keyword(s):  
Failure Time ◽  
Dirichlet Distribution ◽  
Survival Function ◽  
Fixed Time ◽  
Bayes Estimation ◽  
Time Interval ◽  
Failure Rates ◽  
Failure Time Distribution ◽  
Accelerated Life ◽  
Bayesian Nonparametric Estimation

The failure time distribution is estimated in the nonparametric context when some of tbe observations arc censored. The time interval is partitioned into fixed class intervals, and number of failures and number censored in each of these intervals are observed. Using a Dirichlet distribution as the prior, the resulting estimates of the survival function and the failure rate have a nice and simple form. If instead of the fixed time intervals, one uses the “natural” intervals formed by the observed failure times, this gives essentially the same results as in Ferauson IUld Phadia (1977), Susarla and Van Ryzin (1976), but in a much simpler way. Bayes estimation under the increasins and decreasing failure rates is also considered, and applications to accelerated life testing are discussed.

Sample selection of prognostics validation test based on multi-stage Wiener process

2018 ◽  
Vol 233 (4) ◽  
pp. 605-614
Author(s):  
Zhiao Zhao ◽  
Yong Zhang ◽  
Guanjun Liu ◽  
Jing Qiu
Keyword(s):  
Wiener Process ◽  
Process Model ◽  
Failure Modes ◽  
Early Stage ◽  
Sample Selection ◽  
Degradation Process ◽  
Time Interval ◽  
Degradation Data ◽  
Multi Stage ◽  
Selection Of

Sample allocation and selection technology is of great significance in the test plan design of prognostics validation. Considering the existing researches, the importance of prognostics samples of different moments is not considered in the degradation process of a single failure. Normally, prognostics samples are generated under the same time interval mechanism. However, a prognostics system may have low prognostics accuracy because of the small quantity of failure degradation and measurement randomness in the early stage of a failure degradation process. Historical degradation data onto equipment failure modes are collected, and the degradation process model based on the multi-stage Wiener process is established. Based on the multi-stage Wiener process model, we choose four parameters to describe different degradation stages in a degradation process. According to four parameters, the sample selection weight of each degradation stage is calculated and the weight of each degradation stage is used to select prognostics samples. Taking a bearing wear fault of a helicopter transmission device as an example, its degradation process is established and sample selection weights are calculated. According to the sample selection weight of each degradation process, we accomplish the prognostics sample selection of the bearing wear fault. The results show that the prognostics sample selection method proposed in this article has good applicability.

The influence of water temperature and pH on the survival of Fasciola hepatica miracidia

Parasitology ◽  
1984 ◽  
Vol 88 (1) ◽  
pp. 97-104 ◽  
Author(s):  
G. Smith ◽  
B. T. Grenfell
Keyword(s):  
Maximum Likelihood Method ◽  
Fasciola Hepatica ◽  
Good Description ◽  
Survival Function ◽  
Experimental Studies ◽  
Likelihood Method ◽  
Confidence Limits ◽  
Mean Values ◽  
Influence Of Water ◽  
The Mean

SUMMARYExperimental studies on the survival of Fasciola hepatica miracidia show no evidence that miracidial mortality varies with the pH of the medium, at least in the range 6·0–8·0. On the other hand, miracidial mortality is shown to vary with both the temperature of the medium and the age of the larvae. The mean expected life-span of the miracidium decreases from about 35 h at 6°C to about 6° h at 25° C. The Gompertz survival function provides a good description of the miracidial survivorship curves over the range of temperatures used, and we describe, a maximum likelihood method of estimating the mean values of the parameters of this function, together with their approximate 95% confidence limits.

A degradation model for maintenance improvement in respect of cost and availability

2015 ◽  
Vol 21 (1) ◽  
pp. 55-69 ◽  
Author(s):  
Christophe Letot ◽  
Pierre Dehombreux ◽  
Edouard Rivière-Lorphèvre ◽  
Guillaume Fleurquin ◽  
Arnaud Lesage
Keyword(s):  
Preventive Maintenance ◽  
Residual Life ◽  
Operating Time ◽  
Hitting Times ◽  
Mean Residual Life ◽  
Reliability Model ◽  
Content Type ◽  
Degradation Data ◽  
Specific Item ◽  
The Mean

Purpose – The purpose of this paper is to highlight the need for degradation data in order to improve the reliability and the mean residual life estimation of a specific item of equipment and to adapt the preventive maintenance tasks accordingly. Design/methodology/approach – An initial reliability model which uses a degradation-based reliability model that is built from the collection of hitting times of a failure threshold. The proposed maintenance model is based on the cost/availability criterion. The estimation of both reliability and optimum time for preventive maintenance are updated with all new degradation data that are collected during operating time. Findings – An improvement for the occurrences of maintenance tasks which minimizes the mean cost per unit of time and increases the availability. Practical implications – Inspection tasks to measure the degradation level should be realized at least one time for each item of equipment at a specific time determined by the proposed methodology. Originality/value – The introduction of a criterion which helps the maintainer to decide to postpone or not the preventive replacement time depending on the measured degradation level of a specific item of equipment.

Failure of Rubber by Abrasion

1985 ◽  
Vol 58 (3) ◽  
pp. 653-661 ◽  
Author(s):  
Carl T. R. Pulford
Keyword(s):  
Abrasive Wear ◽  
Physical Model ◽  
Abrasion Resistance ◽  
Short Review ◽  
Wear Model ◽  
Fracture Properties ◽  
Tire Wear ◽  
Physical Principles

Abstract This short review presents the landmark discoveries and ideas in rubber abrasion that have brought the field to where it is today. First, the important features of rubber abrasion are reviewed as background for a physical model for the abrasion of rubber. The model, due to Thomas, is described in detail, since it clearly shows the connection between the failure of rubber by abrasive wear and the appropriate rubber fracture properties. The implications of the model for improved abrasion resistance are also discussed. Then, physical principles are applied to the failure of rubber by abrasion in actual products, such as tires. The tire wear model of Schallamach and Turner is described, together with its success in explaining several features of tire wear.

The probability that the largest observation is censored

1993 ◽  
Vol 30 (03) ◽  
pp. 602-615 ◽  
Author(s):  
R. A. Maller ◽  
S. Zhou
Keyword(s):  
Survival Time ◽  
Failure Time ◽  
Sufficient Conditions ◽  
Random Variables ◽  
Consistent Estimator ◽  
Survival Times ◽  
Practical Difficulty ◽  
Independent Censoring ◽  
The Mean ◽  
Necessary And Sufficient

Suppose n possibly censored survival times are observed under an independent censoring model, in which the observed times are generated as the minimum of independent positive failure and censor random variables. A practical difficulty arises when the largest observation is censored since then the usual non-parametric estimator of the distribution of the survival time is improper. We calculate the probability that this occurs and give necessary and sufficient conditions for this probability to converge to 0 as n →∞. As an application, we show that if this probability is 0, asymptotically, then a consistent estimator for the mean failure time can be found. An almost sure version of the problem is also considered.

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