Constructing the Parametric Failure Function of the Temperature Control System of Induction Crucible Furnaces

Demin, Dmitriy

doi:10.21303/2461-4262.2020.001489

Cited by 9 publications

(12 citation statements)

References 12 publications

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“…The study is based on the concept proposed in [13] that the composition of the slag can be used to determine the deviation of the melting temperature from normal. The schematic diagram of temperature control is shown in Fig.…”

Section: Materials and Methods Of Researchmentioning

confidence: 99%

“…For the study, let's use data on the content of SiO 2 (%), FeO (%), MnO (%) in slags from [13]. After processing the data to check the limits of applicability of the classifying rule, the results of [15] were used, while the data were extrapolated to the low-temperature region and equations ( 1)-(3) were used:…”

Section: Materials and Methods Of Researchmentioning

confidence: 99%

“…The complete algorithm for calculating the parameters of the classifying rule is given in [13], Table 1 shows the initial data for constructing a classifying rule.…”

Section: Engineeringmentioning

confidence: 99%

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Classification Rule for Determining the Temperature Regime of Induction Gray Cast Iron

Stanovska

Duhanets²,

Prokopovych

et al. 2021

Eureka: PE

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The complexity of using instruments for measuring the technological parameters of induction melting in a continuous mode, and sometimes the impossibility of this, requires the creation of reliable indirect methods for assessing the numerical values of these parameters. This is especially important for quality control of control systems that ensure a given melting temperature regime. The paper proposes a classification rule based on parametric classification methods, which makes it possible to determine the temperature regime of induction melting based on the SiO2 content in the slag and the distribution coefficient. Checking the classifying ability of the obtained rule showed that it is high, since for all the numerical data of the factor-signs, both the high-temperature and low-temperature modes were classified correctly. The restrictions on the application of the classification rule are shown, among them: the restrictions imposed by the range of variation of the values of the attribute factors, and the restrictions imposed by the small sample of the initial data, as well as the arbitrary area of their distribution in the space of the factor-attributes. The rule is presented in a normalized form, and also converted to natural form for ease of practical use. Application of the rule can be recommended to technologists of metallurgical production of foundries to check the compliance of the technological process operations with the specified melting regulations. It can also be used to diagnose processes or temperature control systems that determine the quality of the resulting cast iron. To do this, it is enough to substitute the actual values of SiO2, and Kd into the classification rule. The value of the distribution coefficient Кd is calculated according to the actual data on the content of FeO and MnO in the slag

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Section: Materials and Methods Of Researchmentioning

confidence: 99%

Section: Materials and Methods Of Researchmentioning

confidence: 99%

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Classification Rule for Determining the Temperature Regime of Induction Gray Cast Iron

Stanovska

Duhanets²,

Prokopovych

et al. 2021

Eureka: PE

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show abstract

“…Separation of points (b 0 (τ), b 1 (τ)) in the space of variables b 0 (τ)-b 1 (τ) according to the obtained clusters is possible, for example, by parametric classification [16].…”

Section: Chemistrymentioning

confidence: 99%

Adaptive technology for constructing the kinetic equations of reduction reactions under conditions of a priori uncertainty

Demin¹,

Domin

2021

Eureka: PE

Self Cite

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The object of research is the process of oxide reduction in a reaction system of mass m due to the reaction on a contact surface with an area of S. An adaptive technology is proposed that allows one to construct the kinetic equation of the process in which the oxide is reduced from the initial product under conditions of a priori uncertainty. A priori uncertainty regarding the behavior of a physicochemical system is understood as the fact that the following information is not available to the researcher: – about the change in the mass of the reaction system and the area of the contact surface; – about the rate of accumulation of the finished product; – about the time of withdrawal of the finished product from the system. The proposed adaptive technology includes five sequential stages to eliminate a priori uncertainty. This is ensured through the use of an adaptive algorithm, which allows obtaining the maximum accuracy in estimating the output variable by selecting the optimal parameter of the adaptive algorithm, and the subsequent canonical transformation. The introduced concept "canonical transformation of the kinetic equation" has the following meaning: having received some adequate description of the kinetic equation in a Cartesian coordinate system, a transformation is carried out that allow representing the equation in a new Cartesian coordinate system in such a way that its structure corresponds to the canonical form. The basic postulate of chemical kinetics can be such a canonical type.

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“…Also important are not only the out-of-furnace treatment processes, but also the technologies of iron smelting, which form the chemical composition of the alloy [15]. Depending on the chemical composition of the alloy, the best of the alternative options [16] of impact on the melt is selected, which ensures its optimal characteristics.…”

Section: Introductionmentioning

confidence: 99%

Selection of Optimal Al–si Combinations in Cast Iron for Castings for Engineering Purposes

et al. 2021

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In this work, the optimal combinations of Al – Si in cast iron for cast parts for machine-building purposes were determined with the aim of subsequent selection of rational modes of modification and alloying, and the possibility of their implementation under industrial smelting conditions was checked. The graphical dependence Si=f (Al) is obtained, which is a set of optimal combinations of the content of Al and Si in cast iron, providing the maximum ultimate tensile strength UTS≈245 ... 334 MPa. The technological audit of the results of serial industrial smelting included the analysis of actual indicators, the calculation of sample distribution functions (mathematical expectation and dispersion) of the Al and Si content in the alloy, as well as the UTS value. The correspondence of the indicators of the content of Al and Si and the value of σ to the optimal values was assessed by testing the statistical hypotheses: H: M(Al)=Alopt, M(Si)=Siopt, M(σв)=σвopt.On the basis of the obtained results of the assessment of statistical characteristics and verification of hypotheses, it was established that at the chosen significance level α=0.05, the technological process of smelting satisfies the requirements of optimality in terms of the Si content, but in terms of the Al content, the technological process does not meet the requirements of optimality. The proposed procedure for choosing the optimal combinations of Al and Si makes it possible to choose the amount of correcting additives depending on the actual indicators of the chemical composition during the smelting process. To do this, it is necessary to assess the closeness of the actual composition to the optimal curve Si=f(Al) and choose the one that most satisfies the criteria of rationality. The latter can be the cost of ferroalloys, through which Al and Si are introduced

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Constructing the Parametric Failure Function of the Temperature Control System of Induction Crucible Furnaces

Cited by 9 publications

References 12 publications

Classification Rule for Determining the Temperature Regime of Induction Gray Cast Iron

Classification Rule for Determining the Temperature Regime of Induction Gray Cast Iron

Adaptive technology for constructing the kinetic equations of reduction reactions under conditions of a priori uncertainty

Selection of Optimal Al–si Combinations in Cast Iron for Castings for Engineering Purposes

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