CN115069791A - Strip steel wave-shaped defect online judgment method and system - Google Patents
Strip steel wave-shaped defect online judgment method and system Download PDFInfo
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Abstract
The invention relates to a strip steel wave-shaped defect online judging method and a strip steel wave-shaped defect online judging system, which comprise the following steps: acquiring flatness data of the strip steel on line to form a flatness data set; analyzing the flatness data set to determine a wave-shaped identification area and wave-shaped defect information of the strip steel; determining the wave-shaped defect type of a specific position of the strip steel and counting the occurrence frequency of each wave-shaped defect type; and determining the defects of the whole strip steel according to the wave lengths between the positions of the wave defect types and the occurrence frequency of each wave defect type at any length position of the strip steel. The technical scheme of the invention solves the problem that the plate shape quality cannot be accurately evaluated and controlled due to the fact that the plate shape wave defect cannot be identified on line in the rolling production of the strip steel, avoids the plate shape cloud chart display defect, can accurately display the actual value of the flatness peak value, avoids the problem of strip steel wave misjudgment, can accurately lock the position of the strip steel wave defect, and effectively quantizes the wave defect.
Description
Technical Field
The invention belongs to the field of strip steel rolling, and particularly relates to a strip steel wave-shaped defect online judgment method and system.
Background
In the production process of strip steel products, the quality of the plate shape is always a major concern on site. At present, the technical indexes of the strip steel section contour quality statistics basically have unified quantification standards, online statistics can be carried out by using a computer, and the strip steel wave defect judgment and statistics still need to depend on manual experience, namely, an operator or a technician judges the type of the wave defect according to an operation room plate-shaped cloud picture. The strip steel wave shape judging method based on the manual experience is limited in precision, judging results are not favorable for statistics and storage, and the strip shape quality problem is not favorably and scientifically and effectively solved on site.
The existing strip steel wave shape defect judgment has the following technical defects: firstly, the upper limit of a field plate-shaped cloud picture color label is fixed, only a flatness value range can be displayed, the true flatness value cannot be accurately expressed, wave-shaped defects cannot be quantified, and the display defects can also cause the condition of manual misjudgment; secondly, the existing strip steel wave shape judging technology based on manual experience can only realize the judgment of wave shape types, and cannot accurately position wave shape positions and quantify the sizes of wave shape defects (wave shape length, flatness peak values and the like); thirdly, the existing strip steel wave shape judging technology based on manual experience cannot carry out systematic statistics and record on the wave shape judging result, and the workload of field operators and process responsible persons is increased.
Disclosure of Invention
In order to overcome the problems in the prior art, the invention provides a strip steel wave shape defect online judging method and a strip steel wave shape defect online judging system, which are used for solving the problems in the prior art.
The strip steel wave-shaped defect online judging method comprises the following steps:
s1, acquiring flatness data of strip steel on line to form a flatness data set;
s2, analyzing the flatness data set to determine a wave shape recognition area and wave shape defect information of the strip steel;
s3, determining the wave-shaped defect type of any length position of the strip steel according to the wave-shaped recognition area and the wave-shaped defect information, and counting the occurrence frequency of each wave-shaped defect type;
and S4, determining the defects of the whole strip steel according to the wave length between the positions of the wave defect types and the occurrence frequency of each wave defect at any length position of the strip steel.
In the above aspect and any possible implementation manner, there is further provided an implementation manner, in S1, the strip flatness data is obtained through an online multifunctional instrument, a strip shape instrument or a strip shape control system.
The above-mentioned aspect and any possible implementation manner further provide an implementation manner, and the step S2 of determining the wave-shaped identification area of the strip steel includes: and judging the number of channels of the flatness data corresponding to the length position of each strip steel, counting the frequency of the number of the channels in the flatness data set of the whole roll of strip steel, taking the number of the channels with the most frequency as the number of the channels of the flatness data of the strip steel, and determining a wave-shaped identification area according to the determined number of the channels.
The above-described aspect and any possible implementation manner further provide an implementation manner, where the determining the waveform identification area according to the number of channels includes: firstly, determining the positions of an operation side and a transmission side, and for the flatness data of 9 channels, defining three channel areas at the most center along the width direction of the strip steel as a Zhonglang identification area; two channels on two adjacent sides of the Zhonglang recognition area are rib-lang recognition areas; two channel areas at the most edge part of the strip steel in the width direction are edge wave identification areas; for the flatness data of 7 channels, a channel area at the center in the width direction of the strip steel is specified as a Zhonglang recognition area; two channels on two sides of the middle wave identification area are rib wave identification areas; two channel areas at the most edge part along the width direction of the strip steel are edge wave identification areas; for the flatness data of 5 channels, a channel area at the center in the width direction of the strip steel is specified as a Zhonglang recognition area; and two channels on two sides of the middle wave identification area are rib wave identification areas, and two channel areas on the most edge part in the width direction of the strip steel are edge wave identification areas.
The above-mentioned aspect and any possible implementation manner further provide an implementation manner, wherein the waveform defect information in S2 includes: the method comprises the following steps of determining the length position and the flatness peak value of the strip steel with the wavy defects, wherein the flatness peak value corresponds to a channel:
s21, determining the flatness maximum value of the strip steel at the length position of any strip steel in the flatness data set along the width direction and the corresponding channel number;
s22, comparing the maximum flatness value with a preset flatness threshold value, and if the maximum flatness value exceeds the threshold value, judging that a wave-shaped defect exists;
s23, locking the length position and the flatness peak value of the strip steel where the wavy defect is located, wherein the flatness peak value corresponds to a channel;
s24, repeating S22 and S23 until the judgment of the flatness data set of the current integral strip steel is finished.
The above-mentioned aspect and any possible implementation manner further provide an implementation manner, where the S3 determines the type of the wave defect at any length position of the strip steel according to the wave identification region and the wave defect information, and includes the following steps:
if the locked flatness peak value appears in the middle wave identification area, judging the strip steel wave-shaped defect at the length position as the middle wave;
if the locked flatness peak value appears in the rib wave identification area, firstly, judging the rib wave identification area on the operation side and the rib wave identification area on the transmission side according to the positions of the operation side and the transmission side; if the locked flatness peak value appears in the transmission side rib wave identification area, judging whether the maximum flatness value of the operation side rib wave identification area exceeds a wave-shaped threshold value or not, if so, judging the strip steel wave-shaped defect at the length position to be double rib waves, and if not, judging the strip steel wave-shaped defect at the length position to be the transmission side rib waves; if the locked flatness peak value appears in the operation side rib wave recognition area, judging whether the maximum flatness value of the transmission side rib wave recognition area exceeds a wave-shaped threshold value or not, and if the maximum flatness value exceeds the flatness threshold value, judging the strip steel wave-shaped defect at the length position to be double rib waves; if the flatness threshold is not exceeded, the strip steel wave-shaped defect at the length position is judged as an operation side rib wave;
if the locked flatness peak value appears in the edge wave identification area, the operation side edge wave identification area and the transmission side edge wave identification area are judged according to the positions of the operation side and the transmission side: if the locked flatness peak value appears in the transmission side wave identification area, judging whether the maximum flatness value of the operation side wave identification area exceeds a wave shape threshold value or not, and if the maximum flatness value exceeds the flatness threshold value, judging the strip steel wave shape defect at the length position as double-side waves; if the locked flatness peak value does not exceed the flatness threshold value, the strip steel wave-shaped defect at the length position is judged as the transmission side edge wave; if the locked flatness peak value appears in the operation side wave identification area, judging whether the maximum flatness value of the transmission side wave identification area exceeds a wave shape threshold value, if so, judging the strip steel wave shape defect at the length position to be double-side wave, and if not, judging the strip steel wave shape defect at the length position to be operation side wave.
The above aspects and any possible implementations further provide an implementation, where the types of wavy defects include: medium wave, single-side wave on the operation side, single-side wave on the transmission side, double-side wave, rib wave on the operation side, rib wave on the transmission side, double-rib wave and no wave-shaped defects.
The above aspect and any possible implementation manner further provide an implementation manner, and the s4. determining the defects of the whole strip steel according to the wave lengths among the wave defect types and the occurrence times of each wave defect at any length position of the strip steel includes the following steps:
s41, calculating the difference between the length position of the strip steel of the current wave-shaped defect type and the length position of the strip steel of the last wave-shaped defect type;
s42, if the difference of the positions is smaller than a wave length threshold value, carrying out wave length accumulation calculation; if the difference of the positions is larger than the wave length threshold value, clearing the wave length and recalculating;
s43, setting wave shape length state Flag 1 And Flag 2 ，Flag 1 Flag being a status Flag when the length of the wave exceeds a length threshold 2 The state identifier is the state identifier when the wave length does not exceed the length threshold value, and the initial value of the state identifier are 0;
s44, when the length of the wave shape exceeds the length threshold value, making Flag 1 Count the number of undulations that exceed the undulation length threshold as 1:
counter＝flag 1 -flag 2
in the formula, the counter is the wave-shaped times;
after the times are calculated, the Flag is enabled 2 1 and counting the current wave length.
When the wave length does not exceed the length threshold, the wave frequency count exceeding the wave length threshold is not started, and the wave length status Flag is set 1 And Flag 2 Keeping an initial value;
s45, repeating the processes from S41 to S44 until the position difference data statistics of the current whole roll of strip steel is completed;
s46, if the wave times exceeding the wave threshold value are larger than 0, determining the integral wave defects of the strip steel as the wave defect types corresponding to the maximum value of the wave defect types counted in the S3; and if the wave-shaped times exceeding the wave-shaped threshold value are equal to 0, judging the coiled strip steel to be free of wave-shaped defects.
The invention also provides an online judging system for the strip steel wave-shaped defects, which comprises the following steps: the data acquisition module is used for acquiring flatness data of the strip steel on line to form a flatness data set;
the first determining module is used for analyzing the flatness data set and determining a wave-shaped recognition area and wave-shaped defect information of the strip steel;
the second determining module is used for determining the wave-shaped defect type of any length position of the strip steel according to the wave-shaped recognition area and the wave-shaped defect information and counting the occurrence frequency of each wave-shaped defect type;
and the third determining module is used for determining the defects of the whole strip steel according to the wave lengths between the positions of the wave defect types and the occurrence frequency of each wave defect at any length position of the strip steel.
The invention also provides a computer storage medium, wherein a computer program is stored on the medium, and the computer program is executed by a processor to realize the online judgment method for the strip wave shape defects.
The invention has the advantages of
Compared with the prior art, the invention has the following beneficial effects:
1) the technical scheme of the invention solves the problem that the plate shape quality cannot be accurately evaluated and controlled due to the fact that the plate shape wave defect cannot be identified on line in the rolling production of the strip steel, avoids the plate shape cloud chart display defect, can accurately display the actual value of the flatness peak value, and avoids the problem of misjudgment of the strip steel wave shape;
2) the technical scheme of the invention can accurately lock the position of the strip steel wave-shaped defect and effectively quantize the wave-shaped defect;
3) the technical scheme of the invention can effectively reduce the labor intensity of field operators and process personnel for recording the wave shape defect problem, systematically counts the wave shape defect while realizing automatic judgment of the wave shape, stores the judgment result into the database, is beneficial to scientifically and effectively solving the plate shape problem, and has good application prospect.
Drawings
Fig. 1 is a schematic flow chart of a strip steel wave shape online determination method according to an embodiment of the present invention;
FIG. 2 is a cloud graph of the strip steel plate shape used in the determination process in the embodiment of the invention;
fig. 3 is a schematic diagram illustrating a waveform identification interval determination rule according to an embodiment of the present invention;
fig. 4 is a schematic diagram of a waveform length statistical algorithm according to an embodiment of the present invention.
Detailed Description
In order to better understand the technical solution of the present invention, the present disclosure includes but is not limited to the following detailed description, and similar techniques and methods should be considered as within the scope of the present invention. In order to make the technical problems, technical solutions and advantages of the present invention more apparent, the following detailed description is given with reference to the accompanying drawings and specific embodiments.
It should be understood that the described embodiments of the invention are only some embodiments of the invention, and not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The terminology used in the embodiments of the invention is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. As used in the description of the invention and the appended claims, the singular forms "a", "an", and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise.
As shown in fig. 1, the method for online determining a strip steel wave defect provided by the embodiment of the present invention includes:
s1, acquiring flatness data of the full-length plate shape of the strip steel from an online multifunctional instrument, a plate shape instrument or a plate shape control system to obtain a flatness data set, wherein the flatness data set comprises the length position of the strip steel and flatness values of all channels in the width direction;
s2, analyzing the flatness data set, and determining a wave-shaped recognition area of the strip steel and determining wave-shaped defect information by adopting a flatness data pattern recognition rule;
the flatness data pattern recognition rule automatically judges the number of data channels by using the channel data characteristics of the shape meter, and divides a wave-shaped recognition area according to the number of the channels;
the strip steel wave defect information comprises a strip steel length position, a flatness peak value and a channel corresponding to the flatness peak value;
s3, determining the wave-shaped defect type of a specific position of the strip steel according to the wave-shaped recognition area and the wave-shaped defect information, and counting the occurrence frequency of each wave-shaped defect type;
and S4, determining the defects of the whole strip steel according to the wave length between the positions of the wave defect types and the occurrence frequency of each wave defect at any length position of the strip steel.
The types of the wavy defects comprise: medium wave, operation side wave, transmission side wave, double side wave, operation side rib wave, transmission side rib wave, double rib wave and no wave defect.
Further, in this embodiment, the flatness data corresponding to each strip steel length position in the flatness data set is determined by using the flatness data pattern recognition rule described in step S2, the number of channels is determined, the frequency of occurrence of each channel number in the whole roll of strip steel flatness data set is counted, and the channel number with the highest frequency of occurrence is used as the channel number of the strip steel flatness data in this embodiment.
Further, in the present embodiment, the flatness data pattern recognition rule is as follows:
assuming that the maximum flatness channel number in the width direction of the strip steel is n, if the flatness data of all channels at a certain length position of the strip steel is a normal value, the flatness data channel number of the strip steel at the position is n; if the flatness data of the 1 st channel and the nth channel is infinite (or infinitesimal) and the data of other channels are normal, the number of the flatness data channels at the position is n-2; if the flatness data of the 2 nd channel and the n-1 st channel is infinitely large (or infinitely small), the number of flatness data channels at the position is n-4; and so on.
Further, the step of determining the waveform identification area of the current strip steel roll by the waveform identification area determination rule in step S2 and the step of determining the waveform defect information are as follows:
B1. determining a wave-shaped recognition area: the operating side and drive side positions are first determined in accordance with the strip processing apparatus, with the lane numbered 1 being closer to the drive side and the lane numbered 9 being closer to the operating side in this embodiment. In the embodiment, the judgment of the wave-shaped identification area is carried out according to the number of the channels and the positions of the transmission side and the operation side, for the flatness data (the width of the strip steel) of the traditional hot continuous rolling 9 channels, 3 channel areas at the center in the width direction of the strip steel are specified as a middle wave identification area, two channels at two adjacent sides of the middle wave identification area are rib wave identification areas, and two channel areas at the edge part in the width direction of the strip steel are edge wave identification areas; for flatness data (the strip steel is narrow) of 7 channels, 1 channel region at the center in the width direction of the strip steel is specified as a middle wave identification region, two channels at two sides of the middle wave identification region are rib wave identification regions, and two channel regions at the edge part in the width direction of the strip steel are edge wave identification regions; for flatness data of 5 channels (the strip steel is extremely narrow), 1 channel area at the center in the width direction of the strip steel is specified as a middle wave identification area, one channel at each of two sides of the middle wave identification area is a rib wave identification area, and two channel areas at the edge part in the width direction of the strip steel are edge wave identification areas.
B2. Judging whether the wave-shaped defects exist or not: and locking the flatness maximum value of any strip steel length position in the flatness data set along the width direction and the corresponding channel number by adopting a maximum flatness maximum value identification algorithm, wherein the algorithm is as follows:
Flat max ＝max{Flat 1 ,Flat 2 ,...,Flat n } (1)
in the formula, Flat max Is the maximum flatness value of each channel at a certain length position of the strip steel, Flat i The flatness value of the ith channel, i.e. the subscript, indicates the number of channels, n is the maximum number of channels, and index is the channel number corresponding to the flatness peak.
In this embodiment, the maximum flatness value is used to determine whether the strip steel at the current length position has a wave-shaped defect. Comparing the flatness maximum value with a flatness threshold value, and if the flatness maximum value exceeds the flatness threshold value, starting a waveform defect judgment rule to judge the waveform defects; and if the flatness threshold value is not exceeded, judging that the length position has no wavy defects.
B3. If the strip steel at a certain length position is judged to have the wave-shaped defects, the length position and the width position of the strip steel with the flatness peak value are locked according to the flatness maximum value and the channel number of the flatness maximum value. And matching the channel number where the flatness maximum value is located with the channel number of each wave-shaped identification area for judging the type of the strip steel wave-shaped defects.
B4. And repeating B2 and B3 until the judgment of the flatness data set of the current coil strip steel is finished.
Further, in the present embodiment, the plate-shaped flatness threshold is set to: the flatness threshold value of the strip steel with the target thickness interval of [1.2mm,2.5mm ] is 30IU, and IU is a standard unit of flatness; the flatness threshold of the strip steel with the target thickness interval of [2.5mm,6mm ] is 25 IU; the flatness threshold value of the strip steel with the target thickness interval of [6mm,26.5mm ] is 10 IU.
Further, the waveform defect type determination rule is as follows:
and if the locked channel where the flatness peak value is located in the middle wave identification area, judging the strip steel wave-shaped defect at the length position as the middle wave.
If the channel where the locked flatness peak value is located in the rib wave identification area, the operation side rib wave identification area and the transmission side rib wave identification area are judged according to the positions of the operation side and the transmission side. If the locked channel where the flatness peak value is located in the transmission side rib wave identification area, judging whether the maximum flatness value of the operation side rib wave identification area exceeds a wave-shaped threshold value or not, if so, judging the strip steel wave-shaped defect at the length position to be transmission side peak value double rib waves, and if not, judging the strip steel wave-shaped defect at the length position to be transmission side rib waves; if the locked channel where the flatness peak value is located in the operation side rib wave identification area, judging whether the maximum flatness value of the transmission side rib wave identification area exceeds a wave shape threshold value or not, if so, judging the strip steel wave shape defect at the length position to be operation side peak value double rib waves, and if not, judging the strip steel wave shape defect at the length position to be operation side rib waves;
if the channel where the locked flatness peak value is located in the edge wave identification area, the operation side edge wave identification area and the transmission side edge wave identification area are judged according to the positions of the operation side and the transmission side. If the locked channel where the flatness peak value is located in the transmission side wave identification area, judging whether the maximum flatness value of the operation side wave identification area exceeds a wave-shaped threshold value or not, if so, judging that the strip steel wave-shaped defect at the length position is judged as the transmission side peak value double-side wave, and if not, judging that the strip steel wave-shaped defect at the length position is judged as the transmission side wave; if the locked channel where the flatness peak value is located in the operation side wave identification area, whether the maximum flatness value of the transmission side wave identification area exceeds a wave shape threshold value or not is judged, if the maximum flatness value exceeds the flatness threshold value, the strip steel wave shape defect at the length position is judged as operation side peak value double-side waves, and if the maximum flatness value does not exceed the flatness threshold value, the strip steel wave shape defect at the length position is judged as operation side waves.
Further, the method for judging the width position of the strip steel comprises the following steps:
Uw＝w÷Ps (1)
in the formula, Uw represents the width of the strip steel covered by a single channel, w is the set width of the strip steel, and Ps is the number of the strip steel channels.
The original point of the position coordinate in the width direction of the strip steel is the central position of the strip steel, and the position coordinate of the width of the strip steel where the flatness peak value is located can be expressed as follows:
P lb ＝(index-n/2-1)Uw (2)
P ub ＝(index-n/2)Uw (3)
in the formula, P 1b Is the lower limit, P, of the interval where the flatness peak is located ub Is the upper limit of the position interval where the flatness peak value is located, and index belongs to [1, n ]]The number of the channel where the flatness peak value is located is n, and the number of the channels with the maximum flatness in the width direction of the strip steel is n.
When the strip steel is judged to be double-side wave or double-rib wave:
SP lb ＝(Ind-n/2-1)Uw (4)
SP ub ＝(Ind-n/2)Uw (5)
in the formula, SP 1b Is the lower limit of the local flatness peak value position of the wave shape identification area at the symmetrical position of the wave shape identification area where the flatness peak value is positioned, SP ub The local flatness peak value position upper limit of the wave shape identification area at the symmetrical position of the wave shape identification area where the flatness peak value is located, wherein the transmission side edge wave identification area and the operation side edge wave identification area are mutually at symmetrical positions, and the transmission side ribThe wave identification area and the operation side rib wave identification area are symmetrical to each other. Ind is the local flatness peak channel number of the flatness peak symmetric location waveform identification zone.
In this embodiment, SP 1b And SP ub The method is used for judging the positions of the wave-shaped peak values of the transmission side and the operation side of the double-side waves or the double-rib waves in the width direction of the strip steel.
In the embodiment, the number of times of the occurrence of the defect types of the strip steel at any length position of the strip steel is counted.
Further, S4, determining the defects of the integral strip steel according to the wave length between the positions of the wave defect types and the occurrence frequency of each wave defect at any length position of the strip steel, wherein the specific calculation process is as follows:
s41, calculating the difference between the length positions of the current wavy strip steel and the last wavy strip steel.
S42, if the position difference is smaller than the wave length threshold value, carrying out wave length accumulation calculation; and if the position difference is larger than the wave length threshold value, clearing the wave length for recalculation.
S43, setting wave shape length state Flag 1 And Flag 2 ，Flag 1 For status flags, Flag, when the length of the wave exceeds a length threshold 2 The state identifier is the state identifier when the wave length does not exceed the length threshold value, and the initial value of the state identifier are 0;
s44, when the length of the wave shape exceeds the length threshold value, making Flag 1 Count the number of undulations that exceed the undulation length threshold as 1:
counter＝flag 1 -flag 2 (6)
in the formula, counter is the wave-shaped times.
After the times are calculated, the Flag is enabled 2 1 and counting the current wave length.
When the wave length does not exceed the length threshold, the wave frequency count exceeding the wave length threshold is not started, and the wave length status Flag is set 1 And Flag 2 The initial value is maintained.
S45, repeating the processes from S41 to S44 until the statistics of the difference data of the positions of the current whole roll of strip steel is completed.
S46, if the wave-shaped times exceeding the wave-shaped threshold value are larger than 0, determining the whole strip steel wave-shaped defects as the wave-shaped defect types corresponding to the maximum value of the wave-shaped defect types counted in the S3; and if the wave-shaped times exceeding the wave-shaped threshold value are equal to 0, judging the coiled strip steel to be free of wave-shaped defects.
According to the strip steel wave shape defect online judging method provided by the embodiment of the invention, strip steel flatness data are acquired online to form a flatness data set; analyzing the flatness data set to determine a wave-shaped identification area and wave-shaped defect information of the strip steel; determining the wave-shaped defect type of a specific position of the strip steel and counting the occurrence frequency of each wave-shaped defect type; and determining the defects of the whole strip steel according to the wave lengths between the positions of the wave defect types and the occurrence frequency of each wave defect type at any length position of the strip steel.
Therefore, the online judgment of the wave shape defect and the locking wave shape position can be realized, the judgment precision can be increased, the working strength of field personnel is effectively reduced, and data support is provided for scientifically solving the problem of the plate shape.
Examples
Obtaining the flatness data of the full length plate shape of a certain strip steel from an online multifunctional instrument, a plate shape instrument or a plate shape control system, selecting the flatness data of the certain strip steel in the embodiment: the bending degree of the strip steel is 1545mm, the length of the strip steel is 527.3m, and the thickness of the strip steel is 4 mm.
The plate cloud of the strip steel in the example is shown in figure 2.
In the method for determining the strip steel wave defect on line, the flatness data pattern recognition rule and the strip steel wave defect determination rule are further used to determine the wave recognition area and the wave defect and lock the position of the wave defect.
Further, in this embodiment, the flatness data corresponding to each strip steel length position is subjected to channel number judgment by using a flatness data pattern recognition rule, the frequency of occurrence of each channel number in the whole roll of strip steel data is counted, and the channel number with the largest frequency of occurrence is used as the channel number of the flatness data of the strip steel of this roll.
Further, in the present embodiment, the flatness data pattern recognition rule is as follows: assuming that the maximum flatness channel number of the strip steel in the width direction is 9, if the flatness data of all channels at a certain length position of the strip steel are normal values, the flatness data channel number of the strip steel at the position is 9; if the flatness data of the 1 st channel and the 9 th channel is infinite (or infinitesimal) and the other channels are normal, the number of the flatness data channels at the position is 7; if the flatness data of the 2 nd and 8 th channels are infinite (or infinite small), the number of flatness data channels at that position is 5; and so on.
In the embodiment, the number of the strip steel channels is finally determined to be 7.
Further, in this embodiment, the rule for determining the waveform identification area is as follows: firstly, determining the positions of an operation side and a transmission side, and for flatness data (the width of strip steel) of a traditional hot continuous rolling 9 channel, specifying that 3 channel areas at the center in the width direction of the strip steel are mid-wave identification areas, two channels at two adjacent sides of the mid-wave identification areas are rib-wave identification areas, and two channel areas at the most edge part in the width direction of the strip steel are edge-wave identification areas; for flatness data (the strip steel is narrow) of 7 channels, 1 channel region at the center in the width direction of the strip steel is specified as a middle wave identification region, two channels at two sides of the middle wave identification region are rib wave identification regions, and two channel regions at the edge part in the width direction of the strip steel are edge wave identification regions; for flatness data of 5 channels (the strip steel is extremely narrow), 1 channel region at the center in the width direction of the strip steel is specified as a middle wave identification region, one channel at each side of the middle wave identification region is specified as a rib wave identification region, and two channel regions at the edge part in the width direction of the strip steel are specified as edge wave identification regions.
In the method for online judging the shape wave defects of the strip steel, the shape wave defect type of any length position of the strip steel is further determined according to the shape wave identification area and the shape wave defect information, and the occurrence frequency of each shape wave defect type is counted.
The number of occurrences of the wave-shaped defect type at any length position of the strip steel in the embodiment is counted as: the middle wave appeared 44 times; side waves were operated 0 times; the transmission side wave appears 0 times; double edge waves appear 0 times; operating side rib waves occurred 0 times; the transmission side rib wave appears 5 times; double billows occurred 12 times.
In the method for judging the strip steel wave-shaped defects on line, the defects of the whole strip steel are further determined according to the length of the strip steel and the occurrence frequency of the wave-shaped defect types at any position of the strip steel.
Further, in this embodiment, as shown in fig. 4, the method for determining the ribbon shape length of the strip is started when the flatness peak of each channel at any length position of the ribbon exceeds the ribbon shape threshold, that is, the calculation is performed after the ribbon shape defect type is determined at a certain position.
The overall wave-shaped defect judgment process of the strip steel is as follows:
C1. and calculating the difference of the length position between the current wavy defect and the last wavy defect of the strip steel.
C2. If the length of the difference between the positions in C1 is less than the waveform length threshold, performing a waveform length accumulation calculation; if the difference between the positions in C1 is greater than or equal to the waveform length threshold, the waveform length is cleared and recalculated.
C3. Wave length setting status Flag 1 And Flag 2 The initial value of the two is 0;
C4. when the wave length exceeds the length threshold, Flag is enabled 1 Count the number of undulations that exceed the undulation length threshold as 1:
counter＝flag 1 -flag 2 (6)
in the formula, counter is the wave-shaped times.
After the times are calculated, the Flag is enabled 2 And 1, counting the length of the current wave shape.
Flag when the wave length does not exceed the length threshold 1 And Flag 2 The initial value is maintained.
C5. And repeating the processes from C1 to C4 until the statistics of the position difference data on the current whole strip steel is completed.
C6. If the wave-shaped times exceeding the wave-shaped threshold value are larger than 0, determining the whole strip steel wave-shaped defects as the wave-shaped defect types corresponding to the maximum value of the counted wave-shaped defect types; and if the wave-shaped times exceeding the wave-shaped threshold value are equal to 0, judging the coiled strip steel to be free of wave-shaped defects. For example, in a strip ribbon shape defect judgment, the frequency of the ribbon shape defects at certain positions of the coiled ribbon steel is as follows: the middle wave appeared 44 times; the unilateral wave on the operation side appears for 0 time; the single edge wave on the transmission side appears for 0 time; double edge waves appear 0 times; operating side rib waves occurred 0 times; the transmission side rib wave appears 5 times; double-rib waves appeared 12 times; the wave length of the 1 st wave is 37.213m, the wave length of the 2 nd wave is 13.512m, and the wave length of more than 10m appears for 2 times; therefore, the coiled strip steel wave defect type is finally judged as a moderate wave.
After the judgment is finished, the program can automatically store the judgment result into the database, so that the workload of field workers is reduced, and the plate shape quality problem is more favorably and scientifically solved.
Preferably, the present invention further provides an online determination system for strip steel wave defects, comprising: the data acquisition module is used for acquiring flatness data of the strip steel on line to form a flatness data set; the data acquisition module includes, but is not limited to, an on-line multifunction instrument, a strip shape instrument, or a strip shape control system.
The first determining module is used for analyzing the flatness data set and determining a wave-shaped recognition area and wave-shaped defect information of the strip steel;
the second determining module is used for determining the wave-shaped defect type of any length position of the strip steel according to the wave-shaped recognition area and the wave-shaped defect information and counting the occurrence frequency of each wave-shaped defect type;
and the third determining module is used for determining the defects of the whole strip steel according to the wave lengths between the positions of the wave defect types and the occurrence frequency of each wave defect at any length position of the strip steel.
Preferably, the present invention also provides a computer storage medium, on which a computer program is stored, the computer program being executed by a processor to perform the online determination method for strip wave shape defects of the present invention.
The foregoing description shows and describes several preferred embodiments of the invention, but as aforementioned, it is to be understood that the invention is not limited to the forms disclosed herein, but is not to be construed as excluding other embodiments and is capable of use in various other combinations, modifications, and environments and is capable of changes within the scope of the inventive concept as expressed herein, commensurate with the above teachings, or the skill or knowledge of the relevant art. And that modifications and variations may be effected by those skilled in the art without departing from the spirit and scope of the invention as defined by the appended claims.
Claims (10)
1. The strip steel wave-shaped defect online judging method is characterized by comprising the following steps:
s1, acquiring flatness data of strip steel of a plate strip on line to form a flatness data set;
s2, analyzing the flatness data set to determine a wave shape recognition area and wave shape defect information of the strip steel;
s3, determining the wave-shaped defect type of any length position of the strip steel according to the wave-shaped recognition area and the wave-shaped defect information, and counting the occurrence frequency of each wave-shaped defect type;
and S4, determining the defects of the whole strip steel according to the wave length between the positions of the wave defect types and the occurrence frequency of each wave defect at any length position of the strip steel.
2. The strip shape defect online judging method according to claim 1, wherein the strip flatness data is obtained by an online multifunctional gauge, a strip shape gauge or a strip shape control system in S1.
3. The strip steel wave defect online judging method according to claim 1, wherein the step S2 of determining the wave identification area of the strip steel comprises: and judging the number of channels of the flatness data corresponding to the length position of each strip steel, counting the frequency of the number of the channels in the flatness data set of the whole roll of strip steel, taking the number of the channels with the most frequency as the number of the channels of the flatness data of the strip steel, and determining a wave-shaped identification area according to the determined number of the channels.
4. The strip steel wave defect online judging method according to claim 3, wherein the determining the wave identification area according to the number of the channels comprises the following steps: firstly, determining the positions of an operation side and a transmission side, and for the flatness data of 9 channels, defining three channel areas at the most center along the width direction of the strip steel as a Zhonglang identification area; two channels on two adjacent sides of the Zhonglang recognition area are rib-lang recognition areas; two channel areas at the most edge part of the strip steel in the width direction are edge wave identification areas; for the flatness data of 7 channels, a channel area at the center in the width direction of the strip steel is specified as a Zhonglang recognition area; two channels on two sides of the middle wave identification area are rib wave identification areas; two channel areas at the most edge part along the width direction of the strip steel are edge wave identification areas; for the flatness data of 5 channels, a channel area at the center in the width direction of the strip steel is specified as a Zhonglang recognition area; and two channels on two sides of the middle wave identification area are rib wave identification areas, and two channel areas on the most edge part in the width direction of the strip steel are edge wave identification areas.
5. The strip wave defect online judging method according to claim 4, wherein the wave defect information in S2 comprises: the method comprises the following steps of determining the length position and the flatness peak value of the strip steel with the wavy defects, wherein the flatness peak value corresponds to a channel:
s21, determining the flatness maximum value of the strip steel at the length position of any strip steel in the flatness data set along the width direction and the corresponding channel number;
s22, comparing the maximum flatness value with a preset flatness threshold value, and if the maximum flatness value exceeds the threshold value, judging that a wave-shaped defect exists;
s23, locking the length position and the flatness peak value of the strip steel where the wavy defect is located, wherein the flatness peak value corresponds to a channel;
s24, repeating S22 and S23 until the judgment of the flatness data set of the current integral strip steel is finished.
6. The strip steel wave defect online judging method according to claim 5, wherein the step S3 of determining the type of the wave defect at any length position of the strip steel according to the wave identification region and the wave defect information comprises the following steps:
if the locked flatness peak value appears in the middle wave identification area, judging the strip steel wave-shaped defect at the length position as the middle wave;
if the locked flatness peak value appears in the rib wave identification area, firstly, judging the rib wave identification area on the operation side and the rib wave identification area on the transmission side according to the positions of the operation side and the transmission side; if the locked flatness peak value appears in the transmission side rib wave identification area, judging whether the maximum flatness value of the operation side rib wave identification area exceeds a wave-shaped threshold value or not, if so, judging the strip steel wave-shaped defect at the length position to be double rib waves, and if not, judging the strip steel wave-shaped defect at the length position to be the transmission side rib waves; if the locked flatness peak value appears in the operation side rib wave identification area, judging whether the maximum flatness value of the transmission side rib wave identification area exceeds a wave-shaped threshold value or not, and if the maximum flatness value exceeds the flatness threshold value, judging the strip steel wave-shaped defect at the length position as double rib waves; if the flatness threshold is not exceeded, the strip steel wave-shaped defect at the length position is judged as an operation side rib wave;
if the locked flatness peak value appears in the edge wave identification area, the operation side edge wave identification area and the transmission side edge wave identification area are judged according to the positions of the operation side and the transmission side: if the locked flatness peak value appears in the transmission side wave identification area, judging whether the maximum flatness value of the operation side wave identification area exceeds a wave shape threshold value or not, and if the maximum flatness value exceeds the flatness threshold value, judging the strip steel wave shape defect at the length position as double-side waves; if the locked flatness peak value does not exceed the flatness threshold value, the strip steel wave-shaped defect at the length position is judged as the transmission side edge wave; if the locked flatness peak value appears in the operation side wave identification area, whether the maximum flatness value of the transmission side wave identification area exceeds a wave shape threshold value or not is judged, if the maximum flatness value exceeds the flatness threshold value, the strip steel wave shape defect at the length position is judged as double-side waves, and if the maximum flatness value does not exceed the flatness threshold value, the strip steel wave shape defect at the length position is judged as the operation side waves.
7. The strip steel wave defect online judging method according to claim 6, wherein the wave defect type comprises: medium wave, single-side wave on the operation side, single-side wave on the transmission side, double-side wave, rib wave on the operation side, rib wave on the transmission side, double-rib wave and no wave-shaped defects.
8. The method for judging the wave defects of the strip steel on line according to the claim 5, wherein the S4. the step of determining the defects of the whole strip steel according to the wave lengths among the wave defect types and the occurrence frequency of each wave defect at any length position of the strip steel comprises the following steps:
s41, calculating the difference between the length position of the strip steel of the current wave-shaped defect type and the length position of the strip steel of the last wave-shaped defect type;
s42, if the difference of the positions is smaller than a wave length threshold value, carrying out wave length accumulation calculation; if the difference of the positions is larger than the wave-shaped length threshold value, clearing the wave-shaped length for recalculation;
s43, setting wave shape length state Flag 1 And Flag 2 ，Flag 1 For status flags, Flag, when the length of the wave exceeds a length threshold 2 The state identifier is the state identifier when the wave length does not exceed the length threshold value, and the initial value of the state identifier are 0;
s44, when the length of the wave shape exceeds the length threshold value, making Flag 1 Count the number of undulations that exceed the undulation length threshold as 1:
counter＝flag 1 -flag 2
in the formula, the counter is the wave-shaped times;
after the times are calculated, the Flag is enabled 2 1 and counting the current wave length.
When the wave length does not exceed the length threshold, the wave frequency count exceeding the wave length threshold is not started, and the wave length status Flag is set 1 And Flag 2 Keeping an initial value;
s45, repeating the processes from S41 to S44 until the position difference data statistics of the current whole roll of strip steel is completed;
s46, if the wave times exceeding the wave threshold value are larger than 0, determining the integral wave defects of the strip steel as the wave defect types corresponding to the maximum value of the wave defect types counted in the S3; and if the wave-shaped times exceeding the wave-shaped threshold value are equal to 0, judging the coiled strip steel to be free of wave-shaped defects.
9. The utility model provides a belted steel wave shape defect online judgement system which characterized in that includes: the data acquisition module is used for acquiring flatness data of the strip steel on line to form a flatness data set;
the first determining module is used for analyzing the flatness data set and determining a wave-shaped recognition area and wave-shaped defect information of the strip steel;
the second determining module is used for determining the wave-shaped defect type of any length position of the strip steel according to the wave-shaped recognition area and the wave-shaped defect information and counting the occurrence frequency of each wave-shaped defect type;
and the third determining module is used for determining the defects of the whole strip steel according to the wave lengths between the positions of the wave defect types and the occurrence frequency of each wave defect at any length position of the strip steel.
10. A computer storage medium having a computer program stored thereon, the computer program being executed by a processor to implement the online determination method for strip wave defect according to any one of claims 1 to 8.
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Effective date of registration: 20240326 Address after: 100083 No. 30, Haidian District, Beijing, Xueyuan Road Patentee after: University OF SCIENCE AND TECHNOLOGY BEIJING Country or region after: China Patentee after: HANDAN IRON & STEEL GROUP Co.,Ltd. Address before: 100083 No. 30, Haidian District, Beijing, Xueyuan Road Patentee before: University OF SCIENCE AND TECHNOLOGY BEIJING Country or region before: China |