Abstract:
Process and equipment for pickling a metal strip, in particular a rolled strip, by means of a pickling plant, through which the metal strip passes and in which the metal strip is pickled using a pickling liquid, the pickling result being a function of pickling parameters. The pickling result is measured and at least one pickling parameter is automatically varied, as a function of the measurement of the pickling result, so as to improve the pickling result.

Description:
FIELD OF THE INVENTION 
     The present invention relates to a process and to equipment for pickling a metal strip, in particular a rolled strip, by means of a pickling plant, through which the metal strip passes and in which the metal strip is pickled using a pickling liquid, the pickling result being a function of pickling parameters. 
     BACKGROUND INFORMATION 
     In order to clean metal strips, in particular in order to remove scale layers on rolled strips, the metal strips are pickled in a pickling plant using a pickling liquid, generally acid. The amount removed by the pickling is a function of pickling parameters. These are, for example: temperature of the pickling liquid, speed at which the metal strip passes through the pickling plant, the acid content in the pickling liquid, the metal content in the pickling liquid, in particular the iron content in the pickling liquid, strip parameters, such as material and geometric dimensions, and the turbulent pressure of the pickling liquid. These pickling parameters have to be set in such a way that as far as possible, the desired amount of material is removed from the metal strip. Deviations from the desired optimum value are associated with high costs. If too much material is removed, i.e., if it is not only the scale layer that is removed from a rolled strip but also metal from the surface of the rolled strip, then the metal or iron content in the pickling liquid is increased to a disproportionate extent. Since the purification of the pickling liquid is complicated and expensive, too high a removal rate is undesirable. In addition, in the event of too high a removal rate, damage to the metal strip may occur. On the other hand, if too much material, in particular too much scale, remains on the metal strip, then this has to pass through the pickling plant again. This additional operation is complicated and expensive. 
     Setting the pickling parameters to achieve the best possible pickling result is conventionally carried out, by an operator of the pickling plant. However, this leads to fluctuations in the pickling result. The pickling result is to be understood, for example, as the amount of material removed or the amount of scale that has remained on the metal strip. 
     SUMMARY 
     An object of the present invention is to provide a process and equipment for pickling a metal strip by means of which the pickling result is improved. Furthermore, it is desirable to reduce the costs for the pickling of a metal strip. 
     According to the present invention, the pickling result is measured and at least one pickling parameter is automatically varied, as a function of the measurement of the pickling result, so as to improve the pickling result. The automatic variation allows the setting of the corresponding pickling parameter by an operator to be dispensed with. In this way, a more constant and better pickling result is achieved. A saving is also made in corresponding operating personnel. The pickling parameters to be set include, for example, the temperature of the pickling liquid in the pickling plant, which is determined, for example, from the temperature of the pickling liquid in the feed into the pickling plant and the temperature of the pickling liquid in the discharge from the pickling plant, the speed of the metal strip, the acid parameters of the pickling liquid, the iron concentration in the pickling liquid, the turbulent pressure of the pickling liquid in the pickling plant and the properties of the metal strip, such as its material and its geometric dimensions. In this case, the temperature of the pickling liquid is the pickling parameter that is particularly suitable for automatic setting. Since the temperature of the pickling liquid in the pickling plant is difficult to measure and difficult to control, use is advantageously made of the feed temperature of the pickling liquid into the pickling plant, the discharge temperature of the pickling liquid from the pickling plant or both temperatures instead of the temperature of the pickling liquid in the pickling plant. 
     The pickling result is advantageously measured by measuring defects and/or unpickled points on the metal strip. The defects and/or unpickled points are advantageously classified and counted. The classification of the defects and/or unpickled points is in this case advantageously carried out in relation to their size and/or their shape. The defects and/or unpickled points classified and counted in this way are advantageously evaluated. The evaluation is carried out using a fuzzy evaluator, a neural network or evaluator a neural fuzzy assessor. However, the measured values can also be evaluated directly, that is to say unclassified, by a fuzzy evaluated, a neural network or a neural fuzzy evaluated, but indirect evaluation, that is to say the evaluation of the classified and counted defects and/or unpickled points, is more advantageous. The result of the evaluation using a fuzzy evaluator, a neural network or a neural fuzzy evaluator are set points for at least one pickling parameter. 
    
    
     BRIEF DESCRIPTION OF THE DRAWINGS 
     FIG. 1 shows a strip plant operated in accordance with the present invention. 
     FIG. 2 shows an arrangement for training an assessor. 
    
    
     DETAILED DESCRIPTION 
     In FIG. 1, reference symbol  1  designates a pickling plant, through which a metal strip  2  passes in the direction of the arrow designated by reference symbol  3 . The metal strip  2  is pickled in the pickling plant  1 , using a pickling liquid. The pickling liquid is fed to the pickling plant  1  from a pickling liquid tank  13  via feed lines  18 ,  19  and a heat exchanger  10 . For the purpose of pickling, the pickling liquid is sprayed against the metal strip  2  from nozzles  6 ,  7 . The pickling liquid running away is intercepted and fed to the pickling liquid tank  13  via a line  20 . 
     The heat exchanger  10  is used for heating the pickling liquid. For this purpose, steam from a steam generator  12  is fed to the heat exchanger  10  via a steam line  16 . The amount of steam can be set via a valve  11 . The steam condenses in the heat exchanger  10 . The water thus produced is fed to the steam generator  12  via a condensate line  17 . 
     The pickling result, i.e. the amount of material removed, or the amount of undesired material, such as scale, for example, that has remained on the metal strip  2 , is a function of pickling parameters. These pickling parameters may be, for example, the temperature of the pickling liquid in the pickling plant  1 , the speed v of the metal strip  1 , the acid parameters c s  of the pickling liquid, the iron concentration c Fe  in the pickling liquid, the turbulent pressure p of the pickling liquid in the pickling plant  1  and the properties B of the metal strip, such as its material and its geometric dimensions. In the present exemplary embodiment, the temperature of the pickling liquid is the only pickling parameter influenced. This is a particularly advantageous configuration, but the pickling result is improved further if further pickling parameters are set in a similar fashion. 
     The temperature T Z  of the pickling liquid in the feed and the temperature T A  of the pickling liquid in the discharge are measured using temperature measuring instruments  9  and  8 . 
     The pickling result is measured by means of an optical measuring instrument  4 . The signal from the measuring instrument  4  is fed to a classifier  5 , in which defects on the metal strip  2  or unpickled points of a material to be pickled away, such as scale, for example, are classified and counted. The defects or points of unremoved material may be classified, for example, in accordance with the defect categories “hole”, “dart spot”, “light spot”, “long dark stripes”, “long bright stripes”, “short dark stripes” and “short light stripes”, in accordance with the following table: 
     
       
         
               
               
             
               
               
               
               
               
             
           
               
                   
                   
               
               
                   
                                          Definition as a function of the speed 
               
             
          
           
               
                 Defect 
                 v = 360 
                 v =  600 
                 v =  1400 
                   
               
               
                 categories 
                 m/min 
                 m/min 
                 m/min 
                 v =  any 
               
               
                   
               
               
                 Hole 
                 Ø ≧ 0.25 
                 Ø ≧ 0.3 
                 Ø &gt; 0.75 
                 — 
               
               
                   
                 mm 
                 mm 
                 mm 
               
               
                 Dark spot 
                 Ø ≧ 0.85 
                 Ø ≧ 1.0 
                 Ø &gt; 1.75 
                 — 
               
               
                   
                 mm 
                 mm 
                 mm 
               
               
                 Light spot 
                 Ø ≧ 0.85 
                 Ø ≧ 1.0 
                 Ø &gt; 1.75 
                 — 
               
               
                   
                 mm 
                 mm 
                 mm 
               
               
                 Long dark 
                 Width 
                 Width 
                 Width 
                 ≧ 0.25 mm 
               
               
                 stripes 
                 ≧0.25 mm 
                 ≧0.25 mm 
                 ≧0.25 mm 
               
               
                 (low 
                 Length 
                 Length 
                 Length 
               
               
                 contrast) 
                  ≧ 3 m 
                  ≧ 5 m 
                 ≧10 m 
               
               
                 Long bright 
                 Width 
                 Width 
                 Width 
                 ≧ 0.25 mm 
               
               
                 stripes 
                 ≧0.25 mm 
                 ≧ 0.25 mm 
                 ≧0.25 mm 
               
               
                 (low 
                 Length 
                 Length 
                 Length 
               
               
                 contrast) 
                  ≧ 3 m 
                  ≧ 5 m 
                 ≧10 m 
               
               
                 Short dark 
                 Width 
                 Width 
                 Width 
                 — 
               
               
                 stripes 
                 ≧ 0.25 mm 
                 ≧ 0.25 mm 
                 ≧ 0.25 mm 
               
               
                 (high 
                 Length 
                 Length 
                 Length 
               
               
                 contrast) 
                 ≧ 15 m 
                 ≧ 20 m 
                 ≧30 m 
               
               
                 Short 
                 Width 
                 Width 
                 Width 
                 — 
               
               
                 bright 
                 ≧ 0.25 mm 
                 ≧ 0.25 mm 
                 ≧ 0.25 mm 
               
               
                 stripes 
                 Length 
                 Length 
                 Length 
               
               
                 (high 
                 ≧ 15 m 
                 ≧ 20 m 
                 ≧30 m 
               
               
                 contrast) 
               
               
                   
               
             
          
         
       
     
     The frequencies of the individual defect categories are fed to an evaluator  15 . This ascertains a set point T Z   ★  for the temperature of the pickling liquid in the feed from the frequencies of the defect categories, from the temperature T A  of the pickling liquid in the discharge, the temperature T Z  of the pickling liquid in the feed, the speed v of the metal strip  2 , the acid parameters c s  of the pickling liquid, the iron concentration c Fe  in the pickling liquid, the turbulent pressure p of the pickling liquid and the properties B of the metal strip  2 . 
     The evaluator  15  is advantageously designed as a fuzzy evaluator, as a neural network or as a neural fuzzy evaluator. In this case, the neural fuzzy evaluator considered is advantageously a neural fuzzy system according to the article “Neuro-Fuzzy”, H.-P. Preuβ, V. Tresp, VDI-Berichte 113, ISBN 3-18-091113-1, 1994, pages 89 to 122. 
     The set points T Z   ★  for the temperature of the pickling liquid in the feed are fed to a controller  14 , which sets the valve  11  as a function of the temperature T Z  of the pickling liquid in the feed and the set point T Z    ★  of the temperature of the pickling liquid in the feed. 
     FIG. 2 shows equipment similar to that in FIG.  1 . However, a set point T Z ★ B  is predefined for the controller  14  by an operator  21 . The set point T Z ★ of the temperature of the pickling liquid in the feed, which is ascertained by the evaluator  15 , does not go into the controller  14 . The equipment according to FIG. 2 has a learning algorithm  23 , by means of which the evaluator  15  ascertains a set point for the temperature in the feed as a function of the set point T Z ★ of the temperature of the pickling liquid in the feed, which is ascertained by the evaluator  15 , of the set point T Z ★ B  of the temperature of the pickling liquid in the feed, which is ascertained by the operator  21 , and as a function of further pickling parameters: temperature T Z  of the pickling liquid in the feed, temperature T A  of the pickling liquid in the discharge, the speed v of the metal strip  2 , the acid parameters C s  of the pickling liquid, the iron concentration c Fe  in the pickling liquid, the turbulent pressure p of the pickling liquid in the pickling plant and the properties B of the metal strip  2 .