scholarly journals Prediction Model and Experimental Study on Braking Distance under Emergency Braking with Heavy Load of Escalator

2020 ◽  
Vol 2020 ◽  
pp. 1-14
Author(s):  
Zhongxing Li ◽  
Haixia Ma ◽  
Peng Xu ◽  
Qifeng Peng ◽  
Guojian Huang ◽  
...  
Keyword(s):  
Prediction Model ◽  
Experimental Studies ◽  
Prediction Method ◽  
Maximum Error ◽  
Heavy Load ◽  
Conservation Of Energy ◽  
Emergency Braking ◽  
Influence Coefficients ◽  
Braking Distance ◽  
Brake Force

In order to study the relationship between the braking distance and the load of escalator and realize the prediction of the rated load braking distance with a little load, the method of combining theoretical analysis and experimental research is used. First, the dynamic characteristics of the escalator during emergency braking are analyzed, and the prediction model of the braking distance of the escalator under different loads is derived based on the law of conservation of energy. Furthermore, the influence coefficients under different loads were determined through experimental studies, the model was revised, and the concept of equivalent no-load kinetic energy (ENKE) was proposed. The research shows that the braking distance of the escalator increases nonlinearly with the increase in load. When the no-load braking distance and the 25% rated load braking distance change greatly, the braking distance increases faster as the load increases; the escalators with large brake force have a small ENKE and are easy to stop. Otherwise, it is difficult to stop. The test results show that the comparison between the predicted value of the prediction model and the measured value has a maximum error of 2.7%, and the maximum error at rated load is only 2.0%, which fully meets the needs of engineering measurement. And the prediction method reduces test costs, enhances test security, and improves test coverage.

Stormwater inflow prediction using radar rainfall data compressed by principal component analysis

2006 ◽  
Vol 1 (1) ◽  
Author(s):  
K. Katayama ◽  
K. Kimijima ◽  
O. Yamanaka ◽  
A. Nagaiwa ◽  
Y. Ono
Keyword(s):  
Principal Component Analysis ◽  
Prediction Model ◽  
Principal Components ◽  
Prediction Method ◽  
Principal Component ◽  
Component Analysis ◽  
Rainfall Data ◽  
Radar Rainfall ◽  
Input Variables ◽  
Inflow Prediction

This paper proposes a method of stormwater inflow prediction using radar rainfall data as the input of the prediction model constructed by system identification. The aim of the proposal is to construct a compact system by reducing the dimension of the input data. In this paper, Principal Component Analysis (PCA), which is widely used as a statistical method for data analysis and compression, is applied to pre-processing radar rainfall data. Then we evaluate the proposed method using the radar rainfall data and the inflow data acquired in a certain combined sewer system. This study reveals that a few principal components of radar rainfall data can be appropriate as the input variables to storm water inflow prediction model. Consequently, we have established a procedure for the stormwater prediction method using a few principal components of radar rainfall data.

scholarly journals Developing an Enhanced Short-Range Railroad Track Condition Prediction Model for Optimal Maintenance Scheduling

2015 ◽  
Vol 2015 ◽  
pp. 1-12 ◽  
Author(s):  
Peng Xu ◽  
Chuanjun Jia ◽  
Ye Li ◽  
Quanxin Sun ◽  
Rengkui Liu
Keyword(s):  
Prediction Model ◽  
Short Range ◽  
Prediction Method ◽  
Maintenance Scheduling ◽  
Railroad Track ◽  
Track Geometry ◽  
Track Maintenance ◽  
Track Condition ◽  
Optimal Maintenance ◽  
Process Work

As railroad infrastructure becomes older and older and rail transportation is developing towards higher speed and heavier axle, the risk to safe rail transport and the expenses for railroad maintenance are increasing. The railroad infrastructure deterioration (prediction) model is vital to reducing the risk and the expenses. A short-range track condition prediction method was developed in our previous research on railroad track deterioration analysis. It is intended to provide track maintenance managers with two or three months of track condition in advance to schedule track maintenance activities more smartly. Recent comparison analyses on track geometrical exceptions calculated from track condition measured with track geometry cars and those predicted by the method showed that the method fails to provide reliable condition for some analysis sections. This paper presented the enhancement to the method. One year of track geometry data for the Jiulong-Beijing railroad from track geometry cars was used to conduct error analyses and comparison analyses. Analysis results imply that the enhanced model is robust to make reliable predictions. Our in-process work on applying those predicted conditions for optimal track maintenance scheduling is discussed in brief as well.

Research on Combined Prediction Model for Busy Telephone Traffic

2014 ◽  
Vol 610 ◽  
pp. 789-796
Author(s):  
Jiang Bao Li ◽  
Zhen Hong Jia ◽  
Xi Zhong Qin ◽  
Lei Sheng ◽  
Li Chen
Keyword(s):  
Prediction Model ◽  
Prediction Accuracy ◽  
Low Frequency ◽  
Prediction Method ◽  
Pso Algorithm ◽  
Frequency Component ◽  
Least Square ◽  
High Frequency Component ◽  
Support Vector ◽  
Telephone Traffic

In order to improve the prediction accuracy of busy telephone traffic, this study proposes a busy telephone traffic prediction method that combines wavelet transformation and least square support vector machine (lssvm) model which is optimized by particle swarm optimization (pso) algorithm. Firstly, decompose the pretreatment of busy telephone traffic data with mallat algorithm and get low frequency component and high frequency component. Secondly, reconfigure each component and use pso_lssvm model predict each reconfigured one. Then the busy telephone traffic can be achieved. The experimental results show that the prediction model has higher prediction accuracy and stability.

scholarly journals A single-station prediction model as a contribution to instantaneous mapping

1994 ◽  
Vol 37 (2) ◽  
Author(s):  
I. Stanislawska
Keyword(s):  
Time Series ◽  
Prediction Model ◽  
Prediction Method ◽  
Physical Processes ◽  
The Past ◽  
Ionospheric Station ◽  
Single Station ◽  
Daily Forecast

The paper presents two opposite approaches for single-station prediction and forecast. Both methods are based on different assumptions of physical processes in the ionosphere and need the different set of incoming data. Different heliogeophysical data, mainly f0F2 parameters from the past were analyzed for f0F2 obtaining for the requested period ahead. In the first method - the autocovariance prediction method - the time series of f0F2 from one station are used for daily forecast at that point. The second method may be used for obtaining f0F2 not only at the particular ionospheric station, but also at any point within the considered area.

scholarly journals Prediction Modeling and Sensitivity Analysis of Robot Bone Milling Temperature Operated by a Doctor

2021 ◽  
Vol 2021 ◽  
pp. 1-17
Author(s):  
Heqiang Tian ◽  
Jingbo Pan ◽  
Yu Gao ◽  
Xiaoqing Dang ◽  
Bin Tian ◽  
...  
Keyword(s):  
Prediction Model ◽  
Cortical Bone ◽  
Cancellous Bone ◽  
Bone Cells ◽  
Prediction Method ◽  
Milling Process ◽  
Milling Parameters ◽  
Cutting Surface ◽  
Milling Temperature ◽  
Cutting Modes

Bone milling is a common method in robot orthopedic surgery. However, excessive milling temperature will cause thermal necrosis of bone cells and tissues. It is necessary to carry out further research and analysis on the robot bone milling process considering the lamina milling skills of spinal surgeons and clinical practice to reduce the damage to bone cells and nearby tissues and obtain good cutting surface quality. Considering the randomness of milling parameters during operation, a prediction method of milling temperature model for ball milling cutter considering the doctor’s surgical skills was proposed based on response surface method. Because of material anisotropy and microstructure difference between the cortical bone and cancellous bone, this paper would analyze the influencing factors in different bone layers to establish the prediction model of milling temperature in the segments of cortical bone and cancellous bone. Also, the influence and distribution of milling parameters on temperature in three cutting modes such as parallel cutting mode, cross cutting mode, and vertical cutting mode in the cortical bone region were analyzed. The parameter sensitivity of the milling temperature prediction model was analyzed by the Sobol method, and the influence of the input parameters on the output milling temperature was analyzed quantitatively.

scholarly journals Simulation Study of the Process of Friction in the Working Elements of a Car Braking System at Different Degrees of Wear

2018 ◽  
Vol 12 (3) ◽  
pp. 221-226 ◽  
Author(s):  
Andrzej Borawski
Keyword(s):  
Simulation Study ◽  
Friction Pair ◽  
Experimental Studies ◽  
Real Life ◽  
Operating Conditions ◽  
Heating Process ◽  
Passenger Cars ◽  
The Road ◽  
Emergency Braking ◽  
Braking System

Abstract Among the many elements of a modern vehicle, the braking system is definitely among the most important ones. Health, and, frequently, life, may rest upon the design and reliability of brakes. The most common friction pair used in passenger cars today is a disc which rotates with the road wheel and a cooperating pair of brake pads. The composite material of the pad results in changing tribological properties as the pad wears, which was demonstrated in experimental studies. The change is also facilitated by the harsh operating conditions of brakes (high and rapid temperature changes, water, etc.). This paper looks into how changing tribology reflects on the heating process of disc and pads during braking. And so a simulation study was conducted, as this method makes it possible to measure temperature in any given point and at any time, which is either impossible or extremely difficult in real life conditions. Finite element method analyses were performed for emergency braking events at various initial speeds of the vehicle reflecting the current road speed limits.

scholarly journals Comparisons Between Braking Experiments and Longitudinal Train Dynamics Using Friction Coefficient and Braking Pressure Modeling in a Freight Train

2020 ◽  
Vol 14 (1) ◽  
pp. 154-163
Author(s):  
Don Bum Choi ◽  
Rag-Gyo Jeong ◽  
Yongkook Kim ◽  
Jangbom Chai
Keyword(s):  
Friction Coefficient ◽  
Time Integration ◽  
Expansion Method ◽  
Dynamics Simulation ◽  
Dynamic Simulations ◽  
Freight Train ◽  
Emergency Braking ◽  
Braking Distance ◽  
Train Dynamics ◽  
Simulation Results

Background: This paper describes the predictions and validation of the pneumatic emergency braking performance of a freight train consisting of a locomotive and 20 wagons, generally operated in Korea. It suggests the possibility of replacing the expensive and time-consuming train running tests with longitudinal train dynamic simulations. Methods: The simulation of longitudinal train dynamics of a freight train uses the time integration method of EN 14531. For reasonable simulation results, the characteristics of the train and brake equipment must be considered. For the train characteristics, specifications provided by the vehicle manufacturer are used. The braking characteristics are analyzed by friction coefficient tests and a braking pressure model. The friction coefficients of a locomotive and wagons are tested with a dynamo test bench and statistically expanded to account for variability. Freight trains should take into account the braking delay time. To reflect this in the simulation, the brake cylinder pressure pattern model uses pressures and exponential empirical equations measured at selective positions in a train of 50 vehicles. The simulation results are validated in comparison with those of the braking tests of a freight train consisting of 1 locomotive and 20 wagons. Results: The results of the longitudinal dynamics simulation show very similar results to the running test results based on the speed profile and braking distance. Conclusion: In particular, the statistical expansion method of the friction coefficient enables robust prediction of the distribution of the braking distance. The simulation can reduce or make up for costly and time-consuming repeated braking tests and reduce the risks that may arise during testing.

Fatigue Life Prediction of Buckling String with Cracks in Horizontal Wells of Mining Engineering

2012 ◽  
Vol 577 ◽  
pp. 127-131 ◽  
Author(s):  
Peng Wang ◽  
Tie Yan ◽  
Xue Liang Bi ◽  
Shi Hui Sun
Keyword(s):  
Fatigue Life ◽  
Prediction Model ◽  
Life Prediction ◽  
Horizontal Well ◽  
Drill Pipe ◽  
Prediction Method ◽  
Drill String ◽  
Fatigue Life Prediction ◽  
Mining Engineering ◽  
Life Prediction Model

Fatigue damage in the rotating drill pipe in the horizontal well of mining engineering is usually resulted from cyclic bending stresses caused by the rotation of the pipe especially when it is passing through curved sections or horizontal sections. This paper studies fatigue life prediction method of rotating drill pipe which is considering initial crack in horizontal well of mining engineering. Forman fatigue life prediction model which considering stress ratio is used to predict drill string fatigue life and the corresponding software has been written. The program can be used to calculate the stress of down hole assembly, can predict stress and alternating load in the process of rotating-on bottom. Therefore, establishing buckling string fatigue life prediction model with cracks can be a good reference to both operation and monitor of the drill pipe for mining engineering.

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