Title of Invention | PROCESS AND DEVICE FOR ONLINE ESTIMATION OF NORMAL SHELL THICKNESS AND DEFORMATION IN BREAKOUT DETECTION SYSTEMS |
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Abstract | The invention provides a process for online estimation of normal shell thickness and deformation in a breakout detection system for controlling operations of a steel continuous caster. The process comprises the steps of inputting thermocouple data and online casting parameters to a plurality of fuzzy fault detection modules, and to an intelligent agent for a comparison of current and virtual standard temperatures to identify the instant of updating current standard temperature by the virtual standard temperature. Collating output from said plurality of fuzzy fault detection modules in terms of a value of a breakoutability in a breakoutability analyzer, and evaluating the fault in terms of type and severity of the fault, its location in terms of layer and thermocouple and its evolution with time for presenting to the operator. The invention also provides a device for carrying out the process. |
Full Text | FIELD OF APPLICATION : The present invention relates to a process and device for online estimation" of normal shell thickness and evaluation of deformity in breakout detection system for controlling operations of a steel continuous caster. The invention provides a process and device for predicting shell deformation and its severity of any type, as they occur, within ambit of a new breakout detection system in a steel continuous casting process. BACKGROUND OF THE INVENTION: The continuous casting process is a fairly recent development in the history of steel making. Before the advent of continuous casting, molten steel used to be solidified into ingots in stationary molds for further processing downstream. The process renders the need for formation of piecewise ingots in isolated events as superfluous. Instead, molten steel now continuously flows into a caster — a copper mold of rectangular cross—section and about a meter length with cooling water flowing around its walls and emerges as a solidified slab to be further cut into discrete lengths. A major technological bottleneck with continuous casting is the occurrence of breakouts. When the molten steel cools in the caster, a semi—solid shell forms at the boundary perimeter of the moving metal (the strand). This hardens and thickens into a shell strong enough to support the Ferro—static pressure of molten steel in the interior, as it emerges out of the caster. Sometimes, the formative shell tears due to friction with the mold - leading to leakage of molten steel and disruption of the casting process. In other cases, the shell develops cracks, OP remains structurally weak — so that molten steel emerges from the fault zone and disrupts casting. In either case, this breakdown of the continuous casting process is called a "breakout" - a very undesirable phenomena that results in many hours of production loss before casting is put back on stream. To prevent occurrence of breakouts in a continuous casting process, breakout detection and prevention systems were developed. A few such systems exist globally. These systems rely on mold wall temperature measurements obtained through thermocouples embedded in the mold wall in horizontal layers, as well as on casting variables like speed, composition of steel, etc. They use various techniques in a processing engine (sitting on a computing platform) to convert these values, in real time, into a binary output which says whether a breakout is likely, or is unlikely, at that instant. This output is passed on to a speed control device, which reduces casting speed to near zero whenever a breakout is predicted - in the process healing the deformity. All occurrence of breakout, as discussed above, can be broadly classified into two types - those caused by shell tear, and those resulting from shell weakness like cracks, depressions, thin- shell deformation, etc. These two types account for more than 95% of all potential breakout, the remaining are due to operational reasons like start—up, slag entrapments,etc. Among these two major types of breakout, those caused by shell weakness - (generally referred to as cracks but also incorporating depressions, thin-sheels and deep oscillation marks), account for about 15%. Most breakout detection systems (BDS) are limited to predicting and preventing stickers, i.e. breakouts resulting from shell tear. The reason is that these are very easy to identify from temperature time—history patterns obtained from the thermocouples. Usually, there are two horizontal layers of thermocouples embedded in the mold walls, and as a tear passes down the mold wall, molten fluid in contact with the wall produces very high temperature readings on the nearest thermocouples. This value returns to normal after the tear has passed. Figure 3 shows four plots, out of these the upper three- show temperature variation with time for three neighboring thermocouples in each layer. The higher temperature (usually) corresponds to a thermocouple from the first layer. The lowest plot shows casting parameters that are not of interest here. As the tear passes the two layers in sequence, the 'rising' phase of temperature at the second layer corresponds to the 'failing' phase from the first layer, and the temperature—history curves intersect and cross. This triggers a breakout alarm. Breakouts resulting from shell weakness are not amenable to such neat identification. As a consequence no existing BBS worldwide can identify these with a high level of certainty. Occasionally, as in the case of a transverse (i.e. horizontal) crack, the temperature recorded by nearest thermocouple show a dip — due to an insulation pocket reducing the heat transfer from strand to mold. This effectively gives rise to an inverse sticker kind of identification — two upper plots. However, the bulk of cracks are longitudinal and not transverse, and other cases of shell weakness, like thin—shells, show no temperature dips at all. Shell—weakness related breakouts can be further classified into two - those that result from localized shell deformities, like cracks, depressions, etc., and those that are characterized by weakness of the formative shell all round the boundary perimeter. The latter is usually a consequence of superheat, low mold level, cooling imbalance or entry of excess slag leading to formation of a slag layer in the strand. The two types may be termed as lcoal shell deformities, and 'perimetric* shell weakness. Perimetric shell weakness is the most difficult to identify, as, at a given instant, there is no standard to compare with. Suppose, at a selected horizontal level, the formative boundary shell is perfectly smooth free of local deformations. What is the guarantee that for the caster under consideration, at this casting speed, carbon percentage and horizontal level, the shell is not thinner than the minimum required for supporting pressure of molten core as the strand proceeds downwards? In other words, for a given caster and associated casting conditions, there exists at every horizontal level a certain characteristic healthy or normal thickness. If this 'virtual' - as it may not exist at this moment — normal thickness can be evaluated; it can be used as a yardstick to measure the current thickness level to evaluate its instantaneous health. There is yet another issue. Even if the virtual normal thickness is known, by what mechanism does one measure the current thickness of such a plastic formative shell in real time ? SUMMARY OF THE INVENTION: The present invention relates to a new and unique method of predicting shell—deformation and its severity, of any type and as they occur, within the ambit of a new breakout detection system. This partially enables the new BDS to progress from the generation that predicts "stickers", to that which predicts "all breakouts". Molten steel proceeding downwards through the cooling mold gradually forms a thin shell at the boundary perimeter that is in near contact with mold walls. This shell thickens and hardens as it moves dawn. Occasionally the formative shell developes deformities that either intensify or diffuse as the shell proceeds. In case of intensification, a breakout can occur when a certain threshold level is crossed. Deformities can be of various types. An increased insulation packet between strand shell and mold wall — and moving with the shell — results in reduced heat transfer in that region leading possibly to a crack. The crack tends to further increase insulation between the shell in its immediate vicinity and the mold wall, leading to its intensification. Alternately, a more spread-out but less intense insulation zone will lead to weaker shell formation initially, which can lead to a thin shell or depression. There is no known mechanism to measure shell thickness distribution at any given vertical location (horizontal level) within a mold, in real time. However, the temperature distribution at that horizontal level bears a close resemblance to the shell thickness distribution. When a crack forms, longitudinal or transverse, the mold wall temperature will be lower and a thermocouple embedded at that location will exhibit the same. A similar condition will be observed for a depression. In case of a thin shell, the molten steel within the shell is closer to the mold wall, as a consequence the corresponding thermocouple will show a higher temperature. Reference to "lower" or "higher* temperatures imply there is a 'standard* temperature against which the comparison is being made. This standard temperature is that which corresponds to the 'average* shell thickness, i.e. if the existing deformities at a horizontal level were, for a moment, all straightened out — then the thickness that would result. It then implies that the standard temperature, analogously, may be obtained simply by taking the mean of temperatures across all thermocouples in a layer. Just as the shell thickness deviates from the "standard thickness* wherever deformities are present, the local thermocouple temperature will also deviate from the 'standard temperature* wherever deformities are present, further, this mapping is direct, i.e. greater the local deformity, higher the temperature deviation. Also, this deviation is descriptive, i.e. negative deviation implies cracks, and positive deviation denotes thin—shells. As the strand moves down in the mold, the 'average' temperature falls, i.e. the mold wall temperature at lower horizontal levels are lower. This is because the temperature gradients between strand shell and the flowing coolant decrease as the shell transverses the mold length and cools. Correspondingly, the reflection of shell deformities into local temperatures also get damped in magnitude (in either positive or negative direction) at lower horizontal layers. A simple way to neutralize this factor - the level effect — is to consider the ratio of local thermocouple temperature to average (i.e. horizontal level) temperature, rather than the directed difference. In the present invention the ratio of local thermocouple temperature to average layer temperature is used as an indicator of shell deformity in the region corresponding to that thermocouple. The above aspect of the invention provides a measure of the deviation from 'normal' , it does not provide the 'normal' shell thickness. A statistical model developed by Vaculik et al (US Patent 6564119) provides 'normal casting conditions' for a known caster and casting parameters; the measure of 'normal shell thickness' can be considered as an element of the total set of 'normal casting conditions". However, to extract the "normal casting conditions' for a given casting mold, at a given casting speed, chemical composition, lubricating powder condition, etc., it takes a few months of data generation from online casting. This has two disadvantages, first, it cannot be implemented from the word 'go' in a new caster, and two, whenever any of the parameters of the model (say speed) occupy values outside its range specified in the data generation phase, the results are likely to be misleading. This brings us to the other aspect of the invention. The other aspect of this invention relates to the establishment of a technique to acquire the "normal shell thickness' with immediate effect, irrespective of caster characteristics and casting parameters. This enables — in company with the first aspect of the invention — the new breakout detection system to measure the degree of deviation of shell perimetric thickness from normal, in real time, and predict the intensity of fault due to shell structural weakness, without any overheads like prior data generation and parameter range limitations. The present invention provides a process for online estimation of normal shell thickness and shell deformation in a breakout detection system for controlling operations of a steel continuous caster, said process characterizead by inputing thermocouple data and online casting parameters to a plurality of fuzzy fault detection modules and to an intelligent agent for a comparison of current and virtual standard temperatures to identify the instant of updating current standard temperature by the virtual standard temperature; collating output from said plurality of fuzzy fault detection modules in terms of a value of a breakoutability in a breakoutability analyzer; and evaluating the fault in terms of type and everity of the fault, its location in terms of layer and thermocouple and its evolution with time for presenting to the operator. The present invention also provides a device for online estimation of normal shell thickness and shell deformation in a breakout detection system for controlling operations of a steel continuous caster, said device comprising thermocouples arranged in mold walls; a plurality of fuzzy fault modules arranged in parallel and an intelligent agent, said plurality of fuzzy fault detection modules and said intelligent agent for receiving data from thermocouple and online casting parameters; and a breakoutability analyzer for collating the outputs from said plurality of fuzzy fault detection modules in terms of a value of breakoutability and for evaluating the fault in terms of severity of the fault, its location in layer or thermocouple and its evolution with time for presenting to the operator. BRIEF DESCRIPTION OF THE ACCOMPANYING DRAWIN6S In the accompanying drawings : Figure 1 shows configuration of a slab caster machine; Figure 2 shows the schematic of thermocouple layout in a typical mold with two layers; Figure 3 shows the temperature time-history pattern of a sticker; Figure 4 shows the temperature time—history for a crack; Figure 5 shows the breakout detection system architecture; Figure 6 shows the fuzzy membership function distribution for temperature ratios; Figure 7 shows the fuzzy membership function distribution identical for both normalized inputs CST and VST; Figure 9a, 8b and 8c show a flow chart of the high level breakout detection system. In case of a true deformity in the shell, the temperature of the corresponding thermocouple will be significantly different from the layer average, and will tend to adversely influence the average and damp its own severity. Hence, when checking each thermocouple for a deformity at its corresponding shell location, the average is calculated without consideration of that thermocouple, i.e. the average is really 'average minus thermocouple of interest'. A wider picture of the present invention can be provided in terms of its role within a continuous caster monitoring and breakout detection system. Figure 5 shows the conceptual architecture of this system. Thermocouple inputs 1 and the online casting parameters are fed to three fuzzy fault detection modules 2,3,4 arranged in parallel. Thermocouple inputs are also provided to an intelligent agent 5. The three fuzzy fault detection modules are sticker detection module 2, crack detection module 3 and thin shell detection module 4. Out of these modules the crack detection module 3 evaluates crack and local thin shells. The present invention fits in this crack detection module 3. Outputs from all these fuzzy fault detection modules 2, 3, 4 in terms of value of breakoutability that effectively represents the supplement of degree of normality in a scale of 0 to 100 is collated in a breakoutability analyzer 6. The breakoutability analyzer 6 evaluates the type and severity of maximum fault, representing a sticker, a crack, local or perimetric thin shell, etc., its location in terms of layer and thermocouple and its evolution with time and presents it to the operator. It may be noted that the input—output feed—forward cycle operates in real- time . Fuzzy logic is considered for all the fault detection modules as this provides a natural way to convert causes of fault into intensity of fault, instead of the usual breakout/no—breakout output paradigm followed in nearly all extant breakout detection systems. In the module of interest, i.e. crack detection, the fuzzy system takes four inputs. Processing control flows over each layer and across each thermocouple in a layer, and the fuzzy analysis module is executed therein for each thermocouple. The output, i.e. breakoutability, again from each thermocouple, is sent to the breakoutability analyzer. The first and most significant of the four inputs to the fuzzy analysis module is the ratio of local thermocouple temperature to the instantaneous average temperature. The other inputs are of a supportive nature and help in refining the value of breakoutability. These are, first, the casting speed, second, the percentage of Carbon, and third, the vertical location. All the fuzzy inputs have a range of existence that depends on physical conditions. These are mapped into the domain {-1:1} far fuzzification using a quadratic transformation. Table 1 describes the four variables, their range of existence and normalization mechanism, and the type and number of fuzzy membership functions. The first input, i.e. temperature ratio, is the driver of breakoutability and also the core of this invention. The membership functions of this variable are shown in more detail in Fig.6. With reference to the other aspect of this invention, in a continuous casting process for steel, the solidification of liquid steel initiates at the strand boundary perimeter - the region nearest to cooling mold walls — and advances inwards even as the strand moves down. For the casting process to be stable, a close relationship needs to be maintained between the mold coolant flux, the casting speed, and the liquid steel entry temperature, with the driving objective that the shell thickness growth rate must be sufficient to be able to support ferro—static pressure of molten core in strand, near the mold bottom. Disturbance in the equilibrium between the above three parameters or the return towards equilibrium from perturbations caused by variation in other casting parameters, will affect shell thickness growth - sometimes to the extend that the driving objective mentioned above may not be attained. This will lead to a breakout. The best way to prevent such a breakout would be to pick up the shell thickness at any horizontal layer of interest, and compare it with an available "normal thicknes'. This "normal", is of course, a strong function of many casting parameters — as discussed in the last section. In following such an approach, the first concern is that there is no available means to pick up shell thickness in real time. However, the average shell thickness around boundary perimeter at a given horizontal layer bears a close resemblance to the average temperature of all thermocouples embedded in mold walls at that horizontal level. If the shell becomes thin, then the molten core will be closer to mold wall than usual,and the observed average temperature will be high. The converse for a thicker shell. Also, if a slag layer entrapped in the strand and passes a layer of thermocouple, the reduced heat transfer will reflect in a lower average temperature. Hence, there is a direct relationship between extend of deviation of shell thickness from 'normal thickness', and the degree of divergence of average layer temperature from a 'normal layer temperature'. In other words, one can transform the analysis of shell thickness deviation from normal thickness at a layer, into an analysis of layer average temperature deviation from layer normal temperature. This transformation, and its implementation in the new caster monitoring and breakout detection system, constitute the first aspect of this invention. The second concern is that the 'normal layer temperature* is as etheral an entity as 'normal layer thickness'. Branted that temperatures can be obtained easily from the thermocouple while layer thickness cannot be obtained at all. However, the 'normal layer temperature* is as virtual as 'normal layer thickness' - in the sense that it does not physically exist (unlike instantaneous average temperature) at that point in time. This etheral entity is brought into the inundate plane, i.e. made from virtual, using an intelligent agent — the second part of this invention. For ease of discussion we refer to the 'normal layer temperature" as current standard temperature or CST. As discussed, it is a function of a large number of casting parameters. Under transitory conditions it follows the parameters with a lag, ie. the CST at agiven instant is that which pertains to parametric states at ∆t earlier. When conditions stabilize, the CST stabilizes after time ∆t. The intelligent agent assumes, firstly, that for a given set of values of all casting parameters in a caster, there exists a unique CST. Secondly, the best measure of CST is an average across time of the instantaneous averages across thermocouple (see equation 1 below) of temperature, when casting conditions are stable. The ingenuity of the intelligent agent lies in moving from one set of casting conditions to another, through a transitory phase. To achieve this transition, a virtual standard temperature or VST is defined. This VST is obtained using the above average, i.e. where i denotes summation over past N time steps, j the summation M number of thermocouples at each time step, and T the temperature. If the instantaneous layer average changes suddenly, the VST will reflect this change, but slowly - like the lag in real. If that average changes slowly, the VST will change even more slowly. Thus at any given instant the intelligent agent has a CST and a VST. The CST is the working value of standard temperature - what the caster monitoring and breakout detection system is using at that instant. The VST is a potential CST in the background. Under stable conditions, they match exactly. In transitory states, VST starts deviating from CST. The agent has to decide exactly, when the CST has to be replaced by the VST. That is done by decision making element of the intelligent agent. The decision making element of the intelligent agent is a Takaji Sugeno type fuzzy system. It takes two inputs with a single input - to replace or not to replace. The first input is the absolute value of the difference betwen the CST and VST. Obviously, the larger this value, the larger the compulsion for change. As is any fuzzy system the absolute difference is normalized to {-1:1} through a transform, refer to Table 1. The second input is the absolute value of the rate of change of VST. In fact, it is the temporal average of absolute values of rate of change of VST, taken over a few time steps. When the rate of change of VST is fluctuating, i.e. casting parameters are not changing monotonously, the replacement of CST is impeded. In other words, the CST should not chase such a turbulent VST. When this rate is very low, i.e. VST has stabilized, or is high and monotonous, i.e. VST is rapidly changing to a different level, the change of CST is facilitated. Figure 6 shows the fuzzy membership function distribution of the two inputs — also refer to Table 2. Using this novel approach of picking up normal shell thickness direction from the dynamic casting environment, the need to frame a model based on casting parameters and subsequently train it on a running caster, is made redundant. The evaluated values of normal temperature (current standard temperature) for each layer of thermocouples emanating from the intelligent agent are used in the thin-shell prediction module, where these are combined with the instantaneous average temperatures of the corresponding layers to generate the degree of deviation of shell thickness from normality (refer discussions above). This deviation is the most significant input in the fuzzy thin-shell module, where it is combined with three other inputs - the casting speed, percentage of Carbon, and layer vertical position in mold — to generate the breakoutability. The present invention has enabled the new breakout detection system to evaluate in real time and with very good accuracy the nature and intensity of local shell deformities of any kind, as well as the shell perimetric weakness at horizontal levels of interest using the simple well—known mechanism of thermocouple layers at these levels. This facilitates online shell health monitoring with the provision for raising breakout alarms whenever a fault crosses a threshold. WE CLAIM 1. A process for online estimation of normal shell thickness and deformation in a breakout detection system for controlling operations of a steel continuous caster, said process characterized by the steps of: - inputing thermocouple data and online casting parameters to a plurality of fuzzy fault detection modules, and to an intelligent agent for a comparison of current and virtual standard temperatures to identify the instant of updating current standard temperature by the virtual standard temperature; - collating output from said plurality of fuzzy fault detection modules in terms of a value of a breakoutability in a breakoutability analyzer; and - evaluating the fault in terms of type and severity of the fault, its location in terms of layer and thermocouple and its evolution with time for presenting to the operator. 2. The process as claimed in claim 1, wherein the evaluation of severity of the fault is in terms of evaluation of sticker, crack, local or perimetric thin shell. 3. The process as claimed in claim 1, wherein collating the outputs from said plurality of fuzzy fault detection modules is in terms of a value of breakoutability that effectively represents the supplement of degree of normality in a scale of 0 to 100. 4. The process as claimed in claim 1, wherein the fuzzy inputs to said crack detection module comprises ratio of local thermocouple temperature to the Instantaneous average temperature, casting speed, percentage of carbon and vertical location. 5. The process as claimed in claim 4, wherein the ratio of local thermocouple temperature to the instantaneous average temperature is used as an indicator of shell deformity in the region corresponding to that thermocouple. 6. The process as claimed in claim 1, wherein the determination of the severity of fault is by combining the evaluated value of normal temperature (CST) for each layer of thermocouples with the instantaneous thermocouple layer perimetric average temperature. 7. The process as claimed in claim 6, wherein a multi-variable comparison of some functions of the current and virtual standard temperatures, i.e. CST and VST, are made in the intelligent agent to decide on the instant of updating of CST by VST, by using a fuzzy system of Takagi Sugeno type. 8. A device for online estimation of normal shell thickness and shell deformation in a breakout detection system for controlling operations of a steel continuous caster, said device comprising: - thermocouples arranged in mold walls; - a plurality of fuzzy fault detection modules arranged in parallel and an intelligent agent, said plurality of fuzzy fault detection modules and said intelligent agent for receiving data from thermocouple and online casting parameters; and - a breakoutability analyzer for collating the outputs from said plurality of fuzzy fault detection modules in terms of a value of breakoutability and for evaluating the fault in terms of severity of the fault, its location in layer or thermocouple and its evolution with time for presenting to the operator. 9. A process carried out with the help of a device for online estimation of normal shell thickness and shell deformation in a breakout detection system for controlling operations of a steel continuous caster, substantially as herein described and illustrated in the accompanying drawing. |
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420-kol-2004-correspondence-1.1.pdf
420-KOL-2004-CORRESPONDENCE.pdf
420-kol-2004-examination report.pdf
420-kol-2004-granted-abstract.pdf
420-kol-2004-granted-claims.pdf
420-kol-2004-granted-description (complete).pdf
420-kol-2004-granted-drawings.pdf
420-kol-2004-granted-form 1.pdf
420-kol-2004-granted-form 2.pdf
420-kol-2004-granted-specification.pdf
420-kol-2004-reply to examination report.pdf
Patent Number | 247790 | ||||||||||||||||||
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Indian Patent Application Number | 420/KOL/2004 | ||||||||||||||||||
PG Journal Number | 20/2011 | ||||||||||||||||||
Publication Date | 20-May-2011 | ||||||||||||||||||
Grant Date | 18-May-2011 | ||||||||||||||||||
Date of Filing | 16-Jul-2004 | ||||||||||||||||||
Name of Patentee | TATA STEEL LIMITED | ||||||||||||||||||
Applicant Address | JAMSHEDPUR | ||||||||||||||||||
Inventors:
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PCT International Classification Number | G01K7/00 | ||||||||||||||||||
PCT International Application Number | N/A | ||||||||||||||||||
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PCT Conventions:
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