scholarly journals Application of Time-series Analysis in Control of Chemical Composition of Grey Cast Iron

2012 ◽  
Vol 12 (4) ◽  
pp. 171-175 ◽  
Author(s):  
M. Perzyk ◽  
A. Rodziewicz
Keyword(s):  
Time Series ◽  
Cast Iron ◽  
Chemical Composition ◽  
Time Series Analysis ◽  
Melting Process ◽  
Grey Cast Iron ◽  
Series Analysis ◽  
Good Prediction Accuracy ◽  
Wide Range ◽  
Grey Cast

Abstract The aim of the paper was an attempt at applying the time-series analysis to the control of the melting process of grey cast iron in production conditions. The production data were collected in one of Polish foundries in the form of spectrometer printouts. The quality of the alloy was controlled by its chemical composition in about 0.5 hour time intervals. The procedure of preparation of the industrial data is presented, including OCR-based method of transformation to the electronic numerical format as well as generation of records related to particular weekdays. The computations for time-series analysis were made using the author’s own software having a wide range of capabilities, including detection of important periodicity in data as well as regression modeling of the residual data, i.e. the values obtained after subtraction of general trend, trend of variability amplitude and the periodical component. The most interesting results of the analysis include: significant 2-measurements periodicity of percentages of all components, significance 7-day periodicity of silicon content measured at the end of a day and the relatively good prediction accuracy obtained without modeling of residual data for various types of expected values. Some practical conclusions have been formulated, related to possible improvements in the melting process control procedures as well as more general tips concerning applications of time-series analysis in foundry production.

Effects of Chemical Composition on Microstructure and Properties of High Phosphorus Grey Cast Iron Brake Shoe

2021 ◽  
Author(s):  
Chadanuch Khuntrakool ◽  
Somjai Janudom ◽  
Prapas Muangjunburee ◽  
Narissara Mahathaninwong ◽  
Thiensak Chucheep ◽  
...  
Keyword(s):  
Cast Iron ◽  
Chemical Composition ◽  
Grey Cast Iron ◽  
Brake Shoe ◽  
Microstructure And Properties ◽  
High Phosphorus ◽  
Grey Cast

scholarly journals A Brief Introduction to Nonlinear Time Series Analysis and Recurrence Plots

Vibration ◽  
2019 ◽  
Vol 2 (4) ◽  
pp. 332-368 ◽  
Author(s):  
Bedartha Goswami
Keyword(s):  
Time Series ◽  
Time Series Analysis ◽  
Nonlinear Time Series ◽  
Recurrence Plot ◽  
Series Data ◽  
Nonlinear Time Series Analysis ◽  
Recurrence Plots ◽  
Series Analysis ◽  
Wide Range ◽  
Dynamical Features

Nonlinear time series analysis gained prominence from the late 1980s on, primarily because of its ability to characterize, analyze, and predict nontrivial features in data sets that stem from a wide range of fields such as finance, music, human physiology, cognitive science, astrophysics, climate, and engineering. More recently, recurrence plots, initially proposed as a visual tool for the analysis of complex systems, have proven to be a powerful framework to quantify and reveal nontrivial dynamical features in time series data. This tutorial review provides a brief introduction to the fundamentals of nonlinear time series analysis, before discussing in greater detail a few (out of the many existing) approaches of recurrence plot-based analysis of time series. In particular, it focusses on recurrence plot-based measures which characterize dynamical features such as determinism, synchronization, and regime changes. The concept of surrogate-based hypothesis testing, which is crucial to drawing any inference from data analyses, is also discussed. Finally, the presented recurrence plot approaches are applied to two climatic indices related to the equatorial and North Pacific regions, and their dynamical behavior and their interrelations are investigated.

Damage Identification of Simply Supported Beam Bridge Based on Time Series Analysis

2012 ◽  
Vol 236-237 ◽  
pp. 617-621
Author(s):  
Han Bing Liu ◽  
Yan Jun Song ◽  
Guo Jin Tan ◽  
Yan Yi Sun
Keyword(s):  
Time Series ◽  
Time Series Analysis ◽  
Dynamic Response ◽  
Time Domain ◽  
Damage Identification ◽  
Simply Supported Beam ◽  
Simply Supported ◽  
Series Analysis ◽  
Wide Range ◽  
Beam Bridge

Presently, the study on damage identification of bridges is very popular and it has a wide range of applications. Also the related theory and technology are constantly developing and mature. The researches based on the dynamic response of bridge in frequency domain is more, but the dynamics theory is complex and difficult for the engineering personnel to grasp. On the opposite, although the damage identification method based on the dynamic response of bridge in time domain is easy to understand, it is difficulty for applications. The Auto Regressive Moving Average model (ARMA) of time series analysis can be used to settle this problem. It is a not very abstruse theory and it is already apply for the system identification of some Structures. In this paper, we use time series analysis for the damage identification of simply supported beam bridge combined with its own dynamic response in time domain.

CHARACTERISTIC INTERNAL FRICTION SPECTRUM OF GREY CAST IRON

1981 ◽  
Vol 42 (C5) ◽  
pp. C5-929-C5-934 ◽  
Author(s):  
P. Millet ◽  
R. Schaller ◽  
W. Benoit
Keyword(s):  
Cast Iron ◽  
Internal Friction ◽  
Grey Cast Iron ◽  
Grey Cast ◽  
Internal Friction Spectrum
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