Specialized metallurgical processes – compositions for use therei – Processes – Process control responsive to sensed condition
Reexamination Certificate
2001-08-13
2003-08-19
Andrews, Melvyn (Department: 1742)
Specialized metallurgical processes, compositions for use therei
Processes
Process control responsive to sensed condition
C075S382000, C075S384000, C075S387000, C266S080000
Reexamination Certificate
active
06607577
ABSTRACT:
FIELD OF THE INVENTION
This invention relates to a method of determining the amounts of desulphurizing reagents required to reduce the sulphur content in hot metal to meet a specified aim concentration. This method provides tighter control of the process resulting in less reagent usage, higher product yield, and reduced waste material.
BACKGROUND OF THE INVENTION
Hot metal desulphurization, in the iron and steel industry, is the process of adding reactive material to hot metal, mainly molten pig iron, for the purpose of controlling the sulphur content of the product. There are a variety of vessels used to contain the hot metal including specialized rail cars and transfer ladles. The reactive material is typically in a powdered form and is injected into the vessel using a lance. The reagent materials vary in composition but typically have an affinity to form chemical bonds with the sulphur in the molten metal to generate a compound that rises to the top of the vessel. Examples of typical reagents include calcium carbide, magnesium and lime. The addition of reactive material creates a sulphur rich slag layer that can be physically separated from the molten metal that now contains less sulphur.
The amount of sulphur in steel affects the quality of the steel; generally, the more sulphur in the final steel product, the lower the quality. The desulphurization process, in the steel industry, is the process whereby sulphur is removed from the molten metal so that the final steel product will have a sulphur content less than or equal to the maximum sulphur specification for the desired grade/classification of product. For any given grade/classification of product, it is acceptable to have a much lower sulphur content than the maximum specification, but it is not acceptable to have a higher sulphur content. It is important, then, to be able to determine how much reagent will be required to achieve the desired sulphur level predictably and reliably.
Control systems and models exist to determine the amount of reagent to be added. Presently in the Iron and Steel Industry, models for desulphurization use a limited set of process variables. These typically include start sulphur, aim sulphur, temperature and weight of hot metal in the vessel. These systems vary in degrees of automation but typically have automated dispensing equipment for the reagent.
There are no desulphurization reagent prediction or determination systems described in the patent literature. This is because the prior art in this area is quite simplistic and often is manifested in the form of a “hit chart”, which is a table of values for the amounts of reagents required based on the starting sulphur value, the targeted final sulphur value and the weight of hot metal to be desulphurized. These simple tables are often provided by the reagent suppliers and are formulated using simple least squares regression. More sophisticated, automated systems for optimizing reagent determination, of a type similar to the invention described here, have not been documented in the patent or academic literature. The sophistication of the current reagent prediction system improves the precision of the reagent determination, which results in a tighter clustering of the final sulphur values about the targeted values. Based on the prior art, it was often the case that more reagent than necessary would be added to a batch of hot metal in order to guarantee that a majority of the time the maximum allowable final sulphur levels would not be violated. The invention improves the model precision, thereby avoiding the need to add too much reagent to the batch of hot metal. This is advantageous in that savings are realized in reduced reagent costs and also in terms of improved iron yield.
The applicant is aware of prior art in the use of multivariate statistical modeling for the determination and/or prediction of important quantities in other fields. For example, Hu and Root used a multivariate modeling approach to predict a person's disease status using a plurality of disease prediction factors, as described in U.S. Pat. No. 6,110,109. Also, a multivariate prediction equation was used by Barnes et al to determine analyte concentrations in the bodies of mammals as described in U.S. Pat. No. 5,379,764.
The prior art in the area of desulphurization is primarily related to the nature of the reagents themselves, the physical and mechanical apparatus used in the process, and the step-wise procedure for delivering the reagents. An example of prior art in the area of desulphurization reagents is U.S. Pat. No. 5,358,550. An example of prior art in the area of desulphurization physical apparatus is U.S. Pat. No. 4,423,858. An example of prior art in the area step-wise procedures for delivering desulphurization reagents is U.S. Pat. No. 6,015,448. Systems for the determination of the amounts of reagents have not been addressed to date.
SUMMARY OF THE INVENTION
The invention is an on-line system for the determination of reagent usage in hot metal desulphurization processes based on the use of a multivariate statistical model of the type “Projection to Latent Structures” (also known as “Partial Least Squares”, and PLS). The model predicts the amounts of reagents required to control the sulphur content in the hot metal. Additional aspects of the invention deal specifically with on-line system implementation and model adaptation not found in the prior art.
In accordance with the invention, the model uses an extended set of input data beyond the standard sulphur concentrations, including the concentrations of key elements in the hot metal, such as silicon, manganese, and others to determine the appropriate amounts of reagents. The use of the PLS modeling methodology allows all relevant input variables to be included, even if they are highly correlated. The prior art based on least squares regression could not handle correlated inputs and is therefore restricted to a small set of input parameters.
The model output is a set of setpoints, one for each reagent, which are sent to the reagent delivery system that ensures that the specified amounts are injected.
In addition, the invention contains an adaptive component to continuously update the PLS model parameters based on new data records. This allows the model to compensate for shifts and drifts in the process. Furthermore, the invention contains a component to handle missing data in a way that allows reliable predictions to be obtained even when one or more input values are unavailable.
The invention includes the following aspects that arise solely in the case of on-line implementation;
input data validation combined with missing data handling;
post-desulphurization data validation prior to model adaptation;
model adaptation, model validation and updating of the missing data replacement scheme.
It is the application of this modeling technology in its adaptive form to this particular process, along with the use of an extended set of process data as inputs, that is both novel and non-obvious.
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Missing Data methods in PCA and PLS: Score calculations with incomplete observations, Philip R.C. Nelson, Paul A. Taylor, John F. MacGregor, Department of Chemical Engineering, McMaster University, Hamilton, ON, Canada L8S 4L8, Received Jun. 8, 1995; revised Nov. 27, 1995; accepted Jan. 11, 1996.
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McGregor, JF et al: “Statisical Process Control of Multivariate Proce
Dudzic Michael S.
Quinn Shannon L.
Vaculik Vit
Andrews Melvyn
Dofasco Inc.
Schmidt Ingrid E.
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