Reliability Evaluation on Machining Center Based on Three-Parameter Weibull Distribution

2012 ◽  
Vol 430-432 ◽  
pp. 1645-1649 ◽  
Author(s):  
Gong Chang Ren ◽  
Zhi Wei Yang ◽  
Bo Min Meng
Keyword(s):  
Weibull Distribution ◽  
Goodness Of Fit ◽  
Location Parameter ◽  
Least Square Method ◽  
Optimization Method ◽  
Reliability Evaluation ◽  
Least Square ◽  
Distribution Model ◽  
Adaptive Genetic Algorithm ◽  
Machining Center

In order to improve the model accuracy of reliability evaluation, the Three-Parameter Weibull Distribution model of time between fault was established by introducing location parameters. The correlation coefficient optimization method based on the adaptive genetic algorithm was firstly applied to estimate the location parameter of the Three-Parameter Weibull Distribution. Shape parameter and scale parameter were obtained by the least square method. The time between failures of these series machining center submitting to three-parameter weibull Distribution was checked by the test hypothesis of goodness-of-fit distribution. Finally, the machining center was carried out reliability evaluation based on the Three-Parameter Weibull Distribution model.

Reliability Analysis and Goodness-of-Fit Test of Pen Cylinder

2012 ◽  
Vol 522 ◽  
pp. 578-581
Author(s):  
Dan Jiang ◽  
Cong Ling Wang ◽  
Ping Yang
Keyword(s):  
Fatigue Life ◽  
Weibull Distribution ◽  
Goodness Of Fit ◽  
Failure Modes ◽  
Least Square Method ◽  
Least Square ◽  
Life Distribution ◽  
Goodness Of Fit Test ◽  
Durability Test ◽  
Two Parameters

According to the durability test results of pen cylinders, including failure modes and fatigue life data, life distribution of pen cylinder is studied. The parameters of Weibull distribution of pen cylinder are estimated by least square method. Using Weibull distribution test, the goodness-of-fit test of the pen cylinder life distribution is carried out. Results of goodness-of-fit test show fatigue life distribution of pen cylinder complies with Weibull distribution with two parameters.

scholarly journals Linear time-delay circuit and stabilizing controller

2021 ◽  
Vol 2091 (1) ◽  
pp. 012005
Author(s):  
Yuhao Cong ◽  
Yong Zhang ◽  
Guang-Da Hu
Keyword(s):  
Time Delay ◽  
Large Time ◽  
Linear Time ◽  
Least Square Method ◽  
Optimization Method ◽  
Delay System ◽  
Least Square ◽  
Single Chip ◽  
Stabilizing Controller ◽  
Delay Circuit

Abstract This paper is concerned with a linear time-delay circuit and its feedback control. We use electronic components such as resistors and capacitors to realize a linear time-delay system. The time-delays are generated by operational amplifiers and single-chip microcomputers. Based on the actual data measured by the oscilloscope, the parameters of the system are estimated using the least square method. Then a comparison study between the waveform image measured by the oscilloscope and the numerical simulation obtained by MATLAB verifies the effectiveness of the parameters estimations of the circuit system. Furthermore, the circuit system is unstable with a large time-delay, a feedback controller is designed to stabilize the circuit system using the optimization method in the literature. Finally, the experimental results in the linear time-delay circuit show the effectiveness of the optimization method.

Minimum Zone Evaluation of Symmetry Error for Flatness to Flatness Based on the New Generation GPS

2013 ◽  
Vol 662 ◽  
pp. 887-891
Author(s):  
Qian Qian ◽  
Mei Fa Huang ◽  
Huan Yu Li
Keyword(s):  
Least Square Method ◽  
Mathematic Model ◽  
Least Square ◽  
Adaptive Genetic Algorithm ◽  
Machining Error ◽  
Minimum Zone ◽  
New Generation ◽  
Tolerance Method ◽  
The Mathematical Model ◽  
Better Than

Least square method (LSM) is the most popular method used to evaluate machining error nowadays. However, LSM is likely to overestimate the error value, therefore its solution is only approximate and rather than minimum. In order to obtain the minimum, we study the principle of the minimum zone tolerance method (MZT), analyze the characteristics of the new generation GPS, and give the minimum zone mathematic model of the symmetry error for flatness to flatness. For the purpose of optimizing the mathematical model, this paper describes the application of adaptive genetic algorithm to achieve the best estimation. Simultaneously, the process of optimization is realized by MALTAB. Finally, the experiment shows that the evaluation results of MZT is better than evaluation results of LSM.

scholarly journals Results of the Verification of the Statistical Distribution Model of Microseismicity Emission Characteristics

2016 ◽  
Vol 61 (3) ◽  
pp. 489-496
Author(s):  
Aleksander Cianciara
Keyword(s):  
Distribution Function ◽  
Weibull Distribution ◽  
Goodness Of Fit ◽  
Cumulative Distribution Function ◽  
Statistical Distribution ◽  
Cumulative Distribution ◽  
Distribution Model ◽  
Emission Characteristics ◽  
Goodness Of Fit Test ◽  
Empirical Cumulative Distribution Function

Abstract The paper presents the results of research aimed at verifying the hypothesis that the Weibull distribution is an appropriate statistical distribution model of microseismicity emission characteristics, namely: energy of phenomena and inter-event time. It is understood that the emission under consideration is induced by the natural rock mass fracturing. Because the recorded emission contain noise, therefore, it is subjected to an appropriate filtering. The study has been conducted using the method of statistical verification of null hypothesis that the Weibull distribution fits the empirical cumulative distribution function. As the model describing the cumulative distribution function is given in an analytical form, its verification may be performed using the Kolmogorov-Smirnov goodness-of-fit test. Interpretations by means of probabilistic methods require specifying the correct model describing the statistical distribution of data. Because in these methods measurement data are not used directly, but their statistical distributions, e.g., in the method based on the hazard analysis, or in that that uses maximum value statistics.

scholarly journals Different Classical Methods of Estimation and Chi-squared Goodness-of-fit Test for Unit Generalized Inverse Weibull Distribution

2021 ◽  
Vol 50 (5) ◽  
pp. 77-100
Author(s):  
Aidi khaoula ◽  
Sanku Dey ◽  
Devendra Kumar ◽  
Seddik-Ameur N
Keyword(s):  
Weibull Distribution ◽  
Simulation Study ◽  
Goodness Of Fit ◽  
Generalized Inverse ◽  
Real Data ◽  
Least Square ◽  
Data Set ◽  
Inverse Weibull Distribution ◽  
Chi Squared ◽  
New Distribution

In this paper, we try to contribute to the distribution theory literature by incorporating a new bounded distribution, called the unit generalized inverse Weibull distribution (UGIWD) in the (0, 1) intervals by transformation method. The proposed distribution exhibits  increasing and bathtub shaped hazard rate function. We derive some basic statistical properties of the new distribution. Based on complete sample, the model parameters are obtained by the methods of maximum likelihood, least square, weighted least square, percentile, maximum product of spacing and Cram`er-von-Mises and compared them using Monte Carlo simulation study. In addition, bootstrap confidence intervals of the parameters of the model based on aforementioned methods of estimation are also obtained. We illustrate the performance of the proposed distribution by means of one real data set and the data set shows that the new distribution is more appropriate as compared to unit Birnbaum-Saunders, unit gamma, unit Weibull, Kumaraswamy and unit Burr III distributions. Further, we construct chi-squared goodness-of-fit tests for the UGIWD using right censored data based on Nikulin-Rao-Robson (NRR) statistic and its modification. The criterion test used is the modified chi-squared statistic Y^2, developedby Bagdonavi?ius and Nikulin, 2011 for some parametric models when data are censored. The performances of the proposed test are shown by an intensive simulation study and an application to real data set

Novel weights optimization method based on least square method for FPN AND-Rule

2010 ◽  
Vol 24 (7) ◽  
pp. 667-672 ◽  
Author(s):  
Jianxiao Zou ◽  
Houjun Wang ◽  
Jun Shu ◽  
Shicai Fan
Keyword(s):  
Least Square Method ◽  
Optimization Method ◽  
Least Square

Vessel Traffic Flow Distribution Model of Bridge Area Waterway in the Middle Stream of Yangtze River

2014 ◽  
Vol 551 ◽  
pp. 127-133 ◽  
Author(s):  
Hai Qiang Hou ◽  
Yi Cheng Li ◽  
Wei He ◽  
Xing Long Liu
Keyword(s):  
Traffic Flow ◽  
Yangtze River ◽  
Flow Distribution ◽  
Least Square Method ◽  
Least Square ◽  
Distribution Model ◽  
Distribution Rule ◽  
Operating Factor ◽  
Safety Operation ◽  
Vessel Speed

Traffic flow data collection in Wuhan Yangtze River Bridge, locates in the middle of Yangtze River, is help for analysis of the waterway operating factor, which in return increases the capacity in the bridge area waterways and promotes vessel collision avoidance. Traffic flow parameters like vessel speed, arrival time, vessel clearance were collected by manual observation. Through analysis of vessel speed and vessel clearance distribution rule, the vessel speed-clearance model is established based on least square method. Real-time density of ships on navigation, channel utilization and ship safety operation area can be obtained by study on the relationship between speed and shipping space..

Analysis of Bridge Deflection Based on Time Series

2011 ◽  
Vol 71-78 ◽  
pp. 4545-4548 ◽  
Author(s):  
Lei Sun ◽  
Xian Wu Hao
Keyword(s):  
Time Series ◽  
Time Series Analysis ◽  
Goodness Of Fit ◽  
Arima Model ◽  
Least Square Method ◽  
Least Square ◽  
Monitoring Data ◽  
Goodness Of Fit Test ◽  
Bridge Monitoring ◽  
Series Analysis

The bridge health monitoring system can collect large amounts of data, but it lacks the trend analysis of monitoring data. This article introduced the method of Time series analysis into the analysis of bridge monitoring data, and adopted ARIMA model in time series analysis of monitoring data, used the least square method for parameter estimation, established the prediction model for bridge deflection, and conducted the goodness of fit test. Take the actual bridge monitoring data as an example, it was demonstrated that the method is feasible in the prediction of bridge condition trend.

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