Hot rolled steel coil online end shape detection method and system

Abstract

The present invention provides an online end shape detection method and system for hot-rolled steel coils, comprising: denoising measurement data; obtaining a detection baseline based on measurement data fitting; merging the detection baselines on both sides of the steel coil into a curve to obtain a fused curve set; and obtaining measurement results of the overflow edge and tower shape of the steel coil end face based on the fused curve set. The present invention arranges two sets of measurement devices on both sides of the steel coil transport channel, and the laser ranging sensor can automatically rise and fall according to the diameter of the steel coil to ensure that the detection is at a horizontal position at the center of the steel coil. When the steel coil is transported by a conveyor device through the detection area, the laser ranging sensor measures the end face of the steel coil. The measurement results are subjected to steps such as data denoising, baseline fitting, bilateral data fusion, and data extraction to accurately obtain information on the overflow edge tower shape of the steel coil edge.

Description

Technical Field

[0001] The present invention relates to the field of automatic control of metallurgical steel rolling, and in particular to a method and system for online end shape detection of hot-rolled steel coils, and more particularly to a technical solution for achieving real-time online detection of the end shape of hot-rolled strips. Background Art

[0002] Due to the high temperature of hot-rolled steel coils, manual observation and measurement are impossible, resulting in the inability to achieve real-time online measurement of the hot-rolled coil shape.

[0003] Patent document CN207850314U with application number CN201721175897.7 discloses an online detection device for the misalignment of strip coiling, including: a line structured light emitter for projecting line structured light onto the steel coil to be measured; an image acquisition unit for collecting the line structured light reflected from the surface of the steel coil; and an image processing unit for processing the line structured light and obtaining the strip misalignment depth value.

[0004] This patent document uses visual image analysis of the edge of the steel coil to determine whether the coil shape quality is good, but does not fully utilize the information of the overflow edge of the steel coil to help detect the online end shape of the hot-rolled steel coil. Summary of the Invention

[0005] In view of the defects in the prior art, the purpose of the present invention is to provide a method and system for detecting the shape of the end of a hot-rolled steel coil online.

[0006] According to the present invention, a method for detecting the shape of an end of a hot-rolled steel coil online is provided, comprising:

[0007] Step S1: Denoising the measurement data;

[0008] Step S2: obtaining a detection baseline based on the measurement data fitting;

[0009] Step S3: merging the detection reference lines on the two sides of the steel coil into a curve to obtain a fused curve set;

[0010] Step S4: obtaining measurement results of the overflow edge and the pyramid shape of the end face of the steel coil according to the fused curve set.

[0011] Preferably, in step S1:

[0012] Step S1.1: The real-time speed of the strip is converted from an analog quantity to a pulse frequency. The laser ranging sensor measures the distance according to the pulse frequency, obtains the distance measurement result, and performs correction to obtain a set of data with linear correlation;

[0013] The specific method for converting the real-time speed of the strip from analog to pulse frequency is as follows:

[0014]

[0015] s=0~D

[0016] F(s) represents the frequency of analog quantity converted into pulse signal;

[0017] s represents the position of the strip running range relative to the starting point;

[0018] D represents the end point of the strip running range;

[0019] I(s) represents the current analog value corresponding to the real-time speed of the strip, which is an analog value in the valid range of Imin~Imax;

[0020] F 最大 Indicates the maximum frequency corresponding to the real-time speed of the strip;

[0021] Imin represents the current analog value corresponding to the minimum real-time speed of the strip;

[0022] Imax represents the current analog value corresponding to the maximum real-time speed of the strip;

[0023] Imin to Imax is the valid range;

[0024] The specific method of the correction is as follows:

[0025] Using the fixed-distance sampling calibration method, within a distance interval Δs, the coil running speed is considered to be uniform, and the distance measurement results are uniformly corrected by equal intervals. In the Δs interval, after uniform distribution:

[0026] The coordinates of the i+1th measurement point = the coordinates of the i-th measurement point + Δs / N, i = 1, 2, ..., n;

[0027] n is the number of effective points of measurement;

[0028] Step S1.2: Smoothing and filtering are performed on the data in the data set based on the thickness of the strip. Assuming that the thickness of the strip is h, the calculation starts from the first effective distance measurement point, and the distance measurement values are taken at intervals of h / 2. The method of taking the value is to take the average of the measured values between [-h / 2, h / 2] with this point as the center.

[0029] Preferably, in step S2:

[0030] The iterative error method is used to find the baseline of the overflow edge, as follows:

[0031] Assume that the data set after the denoising process in step S1 is (X i , Y i ), i = 1 to n;

[0032] Assume A and B are linear constants, then:

[0033] Y=A+BX

[0034]

[0035]

[0036] X is the coordinate of the measurement point;

[0037] Y is the distance measurement result of the measurement point;

[0038] X i is the coordinate of the i-th measurement point;

[0039] Y i is the distance measurement result of the i-th measurement point;

[0040] The residuals from the least squares fit are:

[0041] The smaller it is, the tighter the observations are focused around the fitted straight line, which means the straight line fits the observations better.

[0042] By eliminating points whose deviation is greater than the threshold, a point set is obtained, and the straight line obtained at this time is used as the detection benchmark.

[0043] Preferably, in step S3:

[0044] Data fusion uses the feature point fitting method, which is as follows:

[0045] The main characteristic points are on the same horizontal line: 2 points on the inner diameter of the steel coil and 2 points on the outer diameter of the steel coil;

[0046] According to the interruptions in the measurement process, the characteristic points of the end faces of both sides of the steel coil are found respectively. According to the least square fitting principle, the fitting parameters of the two straight lines are obtained, and the two curves are merged into one curve.

[0047] Preferably, in step S4:

[0048] When the fused curve set (x i ,y i ), i = 1 ~ n, is the number of effective measurement points, y i The point where S0 is greater than or equal to 0 is considered an abnormal point, thereby obtaining the measurement results of the overflow edge and tower shape of the steel coil end face;

[0049] S0 represents the set deviation reference value. If it exceeds the value, it is not abnormal; if it does not exceed the value, it is normal.

[0050] x iis the coordinate of the i-th measurement point after fusion;

[0051] y i is the ranging result of the i-th measurement point after fusion.

[0052] According to the present invention, a hot-rolled steel coil online end shape detection system is provided, comprising:

[0053] Module M1: De-noising of measurement data;

[0054] Module M2: Get the detection baseline based on the measurement data fitting;

[0055] Module M3: Merge the detection reference lines on the two sides of the steel coil into one curve to obtain a fused curve set;

[0056] Module M4: obtaining measurement results of the overflow edge and the tower shape of the steel coil end surface based on the fused curve set.

[0057] Preferably, in the module M1:

[0058] Module M1.1: Converts the real-time speed of the strip from analog to pulse frequency. The laser ranging sensor measures the distance according to the pulse frequency, obtains the distance measurement result and performs correction to obtain a set of data with linear correlation.

[0059] Among them, the real-time speed of the strip is converted from analog quantity to pulse frequency, as follows:

[0060]

[0061] s=0~D

[0062] F(s) represents the frequency of analog quantity converted into pulse signal;

[0063] s represents the position of the strip running range relative to the starting point;

[0064] D represents the end point of the strip running range;

[0065] I(s) represents the current analog value corresponding to the real-time speed of the strip, which is an analog value in the valid range of Imin~Imax;

[0066] F 最大 Indicates the maximum frequency corresponding to the real-time speed of the strip;

[0067] Imin represents the current analog value corresponding to the minimum real-time speed of the strip;

[0068] Imax represents the current analog value corresponding to the maximum real-time speed of the strip;

[0069] Imin to Imax is the valid range;

[0070] The details of the correction are as follows:

[0071] Using the fixed-distance sampling calibration method, within a distance interval Δs, the coil running speed is considered to be uniform, and the distance measurement results are uniformly corrected by equal intervals. In the Δs interval, after uniform distribution:

[0072] The coordinates of the i+1th measurement point = the coordinates of the i-th measurement point + Δs / N, i = 1, 2, ..., n;

[0073] n is the number of effective points of measurement;

[0074] Module M1.2: Smoothing filter is performed on the data in the data set based on the strip thickness. Assuming that the strip thickness is h, the calculation starts from the first effective distance measurement point, and the distance measurement values are taken at intervals of h / 2. The value selection method is to take the average of the measured values between [-h / 2, h / 2] with this point as the center.

[0075] Preferably, in the module M2:

[0076] The iterative error method is used to find the baseline of the overflow edge, as follows:

[0077] Assume that the dataset denoised by module M1 is (X i , Y i ), i = 1 to n;

[0078] Assume A and B are linear constants, then:

[0079] Y=A+BX

[0080]

[0081]

[0082] X is the coordinate of the measurement point;

[0083] Y is the distance measurement result of the measurement point;

[0084] X i is the coordinate of the i-th measurement point;

[0085] Y i is the distance measurement result of the i-th measurement point;

[0086] The residuals from the least squares fit are:

[0087] The smaller it is, the tighter the observations are focused around the fitted straight line, which means the straight line fits the observations better.

[0088] By eliminating points whose deviation is greater than the threshold, a point set is obtained, and the straight line obtained at this time is used as the detection benchmark.

[0089] Preferably, in the module M3:

[0090] Data fusion uses the feature point fitting method, which is as follows:

[0091] The main characteristic points are on the same horizontal line: 2 points on the inner diameter of the steel coil and 2 points on the outer diameter of the steel coil;

[0092] According to the interruptions in the measurement process, the characteristic points of the end faces of both sides of the steel coil are found respectively. According to the least square fitting principle, the fitting parameters of the two straight lines are obtained, and the two curves are merged into one curve.

[0093] Preferably, in the module M4:

[0094] When the fused curve set (x i ,y i ), i = 1 ~ n, is the number of effective measurement points, y i The point where S0 is greater than or equal to 0 is considered an abnormal point, thereby obtaining the measurement results of the overflow edge and tower shape of the steel coil end face;

[0095] S0 represents the set deviation reference value. If it exceeds the set deviation reference value, it is abnormal; if it does not exceed the set deviation reference value, it is normal.

[0096] x i is the coordinate of the i-th measurement point after fusion;

[0097] y i is the ranging result of the i-th measurement point after fusion.

[0098] Compared with the prior art, the present invention has the following beneficial effects:

[0099] 1. The present invention arranges two sets of measuring devices on both sides of the steel coil transport channel. The laser ranging sensor can automatically rise and fall according to the diameter of the steel coil to ensure that the detection is at the horizontal position of the center of the steel coil.

[0100] 2. When the steel coil is transported by the conveyor through the detection area, the laser ranging sensor measures the end face of the steel coil. The measurement results are subjected to data denoising, benchmark fitting, bilateral data fusion, data extraction and other steps to accurately obtain the overflow edge pyramid information of the steel coil edge.

[0101] 3. The present invention uses a laser rangefinder to detect the edge distance of the steel coil during its advancement, obtains characteristic data information of the overflow edge and tower shape of the steel coil, and performs quality control based on the judgment criteria. BRIEF DESCRIPTION OF THE DRAWINGS

[0102] Other features, objects and advantages of the present invention will become more apparent upon reading the detailed description of non-limiting embodiments with reference to the following drawings:

[0103] Figure 1 This is a schematic diagram of the structure of the steel coil end shape detection device.

[0104] Figure 2 Schematic diagram of the principle of uniformly correcting the distance measurement results through equal spacing.

[0105] Figure 3 Schematic diagram of the principle of data smoothing filtering based on strip thickness.

[0106] Figure 4 Schematic diagram of the principle of obtaining end face feature points.

[0107] Figure 5 This is the end detection flow chart.

[0108] Automatic lifting device 100

[0109] Laser ranging sensor 200 DETAILED DESCRIPTION

[0110] The present invention will be described in detail below with reference to specific embodiments. The following examples will help those skilled in the art to further understand the present invention, but are not intended to limit the present invention in any form. It should be noted that, for those skilled in the art, several changes and improvements can be made without departing from the scope of the present invention. These all fall within the scope of protection of the present invention.

[0111] like Figure 1 As shown, the present invention provides an online end shape detection system for hot-rolled steel coils, comprising: 2 detection towers, 2 laser ranging sensors, 2 sets of lifting devices, 1 control cabinet, and 1 data processing unit.

[0112] When the steel coil passes the previous station in the detection area, the detection system will receive the steel coil diameter information sent by the production line. The lifting device will move up and down according to the steel coil diameter information to ensure that the laser ranging sensor is at the horizontal height position of the center of the steel coil;

[0113] When a coil passes through the inspection area, the inspection system receives a start signal from the production line. Laser rangefinders on both sides of the coil begin detecting the coil simultaneously, capturing raw measurement data in real time. This data is processed to identify coil edge overflow and pyramidal features, enabling quality control based on criteria.

[0114] End measurement process

[0115] Step S1: Data denoising

[0116] Step S1.1: Matching the laser distance sensor with the speed of the steel coil:

[0117] The present invention combines the speed of the steel strip during operation and uses a laser ranging sensor to detect the frequency, thereby converting the real-time speed of the steel strip from an analog quantity to a pulse frequency. The specific method is as follows:

[0118]

[0119] s=0~D

[0120] F(s) represents the frequency of analog quantity converted into pulse signal, unit is Hz;

[0121] s represents the position of the strip running range relative to the starting point;

[0122] D represents the end point of the strip running range;

[0123] For the speed change of the steel coil passing through the detection position, the faster the speed, the higher the frequency, and the slower the speed, the lower the frequency. The frequency is consistent with the movement speed of the steel coil.

[0124] I(s) represents the current analog value corresponding to the real-time speed of the strip, which is an analog value in the valid range of Imin to Imax. The real-time speed of the strip is converted from analog value to pulse frequency.

[0125] F 最大 Indicates the maximum frequency corresponding to the speed;

[0126] Imin represents the current analog value corresponding to the minimum real-time speed of the strip;

[0127] Imax represents the current analog value corresponding to the maximum real-time speed of the strip;

[0128] Imin to Imax is a valid range, for example, Imin to Imax forms a value range of 3-25, in milliamperes.

[0129] Note: After converting the speed represented by the current analog quantity into frequency information, the real-time measurement results detected by the laser ranging sensor can be matched with the running speed of the steel coil, thus creating conditions for subsequent accurate solution.

[0130] The laser ranging sensor collects data at a fixed frequency, so the ranging results need to be corrected according to the actual running speed of the steel coil to ensure that the detection results match the actual measurement position.

[0131] In actual calculation, the present invention adopts a fixed-distance sampling calibration method. Within a sufficiently small distance interval Δs, the running speed of the steel coil can be approximately considered to be uniform. In this way, within this small interval, the distance measurement results can be uniformly corrected by equal spacing.

[0132] like Figure 2 As shown, the distance interval Δs is a sufficiently small distance selected, and points 1# to 7# are the distance measurement results obtained by the laser ranging sensor during this period.

[0133] Assume that the coordinates of measuring point 1# are X(N1#), and the distance measurement result is Y(N1#), which are recorded as x1 and y1 respectively; the other points are numbered in sequence, the coordinates of measuring point 7# are X(N7#), and the distance measurement result is Y(N7#), which are recorded as x7 and y7 respectively.

[0134] In the Δs interval, after uniform distribution, X(N1#)=X(N1#), X(N2#)=X(N1#)+Δs / 6, X(N3#)=X(N2#)+2*Δs / 6, …, X(N7#)=X(N6#)+6*Δs / 6.

[0135] Step S1.2: Data smoothing and filtering based on strip thickness

[0136] After data correction, a set of linearly correlated data was obtained. However, these data presented two challenges: first, the density of the test data obtained at different locations varied due to the varying coil speed; second, there were anomalous data points that needed to be removed during the test process. To address this, a smoothing method was employed that incorporated the strip thickness.

[0137] Assuming the thickness of the strip is h, the calculation starts from the first effective distance measurement point, and the distance measurement values are taken at intervals of h / 2. The method of taking the value is to take the average of the measured values between [-h / 2, h / 2] with this point as the center.

[0138] like Figure 3 As shown: The smoothed value of the point (x3, y3) is (x3, y3 new ):

[0139]

[0140] Step S2: Fitting to obtain the detection benchmark

[0141] Benchmark fitting is to find the baseline of the overflow edge, so as to prepare to characterize the overflow amount.

[0142] Because when there is no overflow edge and tower shape on the edge of the strip, the measurement results follow a linear relationship, and the overflow amount is small and relatively concentrated, the iterative error method is used to find the baseline.

[0143] Iterative error method:

[0144] Assume that the denoised data set is (X i , Y i), i = 1 ~ n, is the number of effective measurement points;

[0145] Let A and B be linear constants, then Y=A+BX

[0146] According to the straight line fitting formula, using the least squares principle, the straight line A and B values are obtained:

[0147]

[0148]

[0149] The residuals from the least squares fit are:

[0150] The smaller it is, the more tightly the observations are concentrated around the fitted straight line, which means that the straight line fits the observations better.

[0151] By removing points with large deviations repeatedly, we can obtain a set of points with small residuals and relatively stable size. The straight line obtained at this time can be used as the detection benchmark.

[0152] Step S3: Fusion of bilateral data

[0153] Because it is easy to obtain the amount of overflow through single-side detection, but the measurement error for the concave points is large, it is necessary to detect on both sides of the steel coil and merge the data from the two sides to more accurately reflect the actual coil shape of the steel coil.

[0154] Data fusion uses feature point fitting method:

[0155] Main characteristic points: 2 points on the inner diameter of the steel coil and 2 points on the outer diameter of the steel coil.

[0156] like Figure 4 As shown in the figure, according to the characteristics of the measurement data, when the end face of the steel coil cannot be measured, the measurement data is displayed as invalid data. From the data curve, it can be seen that the data has obvious interruptions. There are 4 interruptions in the entire measurement process. These 4 interruptions are the characteristic points we need.

[0157] The characteristic points of the end faces on both sides of the steel coil are found respectively. According to the least square fitting principle, the fitting parameters of the two straight lines can be obtained, thereby merging the two curves into one curve.

[0158] Step S4: Data extraction

[0159] When the fused curve set (x i ,y i ), i = 1 ~ n, is the number of effective measurement points, then according to the judgment standard, if more than S0 is an abnormal point, then y iPoints with values greater than S0 are considered abnormal. This allows for measurement of the coil end face's overflow edge and pyramidal shape. S0 represents the set deviation reference value; exceeding it is considered abnormal, while not exceeding it is considered normal.

[0160] According to the present invention, a hot-rolled steel coil online end shape detection system is provided, comprising:

[0161] Module M1: De-noising of measurement data;

[0162] Module M2: Get the detection baseline based on the measurement data fitting;

[0163] Module M3: Merge the detection reference lines on the two sides of the steel coil into one curve to obtain a fused curve set;

[0164] Module M4: obtaining measurement results of the overflow edge and the tower shape of the steel coil end surface based on the fused curve set.

[0165] Preferably, in the module M1:

[0166] Module M1.1: Converts the real-time speed of the strip from analog to pulse frequency. The laser ranging sensor measures the distance according to the pulse frequency, obtains the distance measurement result and performs correction to obtain a set of data with linear correlation.

[0167] Among them, the real-time speed of the strip is converted from analog quantity to pulse frequency, as follows:

[0168]

[0169] s=0~D

[0170] F(s) represents the frequency of analog quantity converted into pulse signal;

[0171] s represents the position of the strip running range relative to the starting point;

[0172] D represents the end point of the strip running range;

[0173] I(s) represents the current analog value corresponding to the real-time speed of the strip, which is an analog value in the valid range of Imin~Imax;

[0174] F 最大 Indicates the maximum frequency corresponding to the real-time speed of the strip;

[0175] Imin represents the current analog value corresponding to the minimum real-time speed of the strip;

[0176] Imax represents the current analog value corresponding to the maximum real-time speed of the strip;

[0177] Imin to Imax is the valid range;

[0178] The details of the correction are as follows:

[0179] Using the fixed-distance sampling calibration method, within a distance interval Δs, the coil running speed is considered to be uniform, and the distance measurement results are uniformly corrected by equal intervals. In the Δs interval, after uniform distribution:

[0180] The coordinates of the i+1th measurement point = the coordinates of the i-th measurement point + Δs / N, i = 1, 2, ..., n;

[0181] n is the number of effective points of measurement;

[0182] Module M1.2: Smoothing filter is performed on the data in the data set based on the strip thickness. Assuming that the strip thickness is h, the calculation starts from the first effective distance measurement point, and the distance measurement values are taken at intervals of h / 2. The value selection method is to take the average of the measured values between [-h / 2, h / 2] with this point as the center.

[0183] Preferably, in the module M2:

[0184] The iterative error method is used to find the baseline of the overflow edge, as follows:

[0185] Assume that the dataset denoised by module M1 is (X i , Y i ), i = 1 to n;

[0186] Assume A and B are linear constants, then:

[0187] Y=A+BX

[0188]

[0189]

[0190] X is the coordinate of the measurement point;

[0191] Y is the distance measurement result of the measuring point;

[0192] X i is the coordinate of the i-th measurement point;

[0193] Y i is the distance measurement result of the i-th measurement point;

[0194] The residuals from the least squares fit are:

[0195] The smaller it is, the tighter the observations are focused around the fitted straight line, which means the straight line fits the observations better.

[0196] By eliminating points whose deviation is greater than the threshold, a point set is obtained, and the straight line obtained at this time is used as the detection benchmark.

[0197] Preferably, in the module M3:

[0198] Data fusion uses the feature point fitting method, which is as follows:

[0199] The main characteristic points are on the same horizontal line: 2 points on the inner diameter of the steel coil and 2 points on the outer diameter of the steel coil;

[0200] According to the interruptions in the measurement process, the characteristic points of the end faces of both sides of the steel coil are found respectively. According to the least square fitting principle, the fitting parameters of the two straight lines are obtained, and the two curves are merged into one curve.

[0201] Preferably, in the module M4:

[0202] When the fused curve set (x i ,y i ), i = 1 ~ n, is the number of effective measurement points, y i The point where S0 is greater than or equal to 0 is considered an abnormal point, thereby obtaining the measurement results of the overflow edge and tower shape of the steel coil end face;

[0203] S0 represents the set deviation reference value. If it exceeds the set deviation reference value, it is abnormal; if it does not exceed the set deviation reference value, it is normal.

[0204] x i is the coordinate of the i-th measurement point after fusion;

[0205] y i is the ranging result of the i-th measurement point after fusion.

[0206] Those skilled in the art will appreciate that, in addition to implementing the system, device, and various modules provided by the present invention in purely computer-readable program code, it is entirely possible to implement the same program in the form of logic gates, switches, application-specific integrated circuits, programmable logic controllers, embedded microcontrollers, and the like by logically programming the method steps. Therefore, the system, device, and various modules provided by the present invention can be considered a hardware component, and the modules included therein for implementing various programs can also be considered structures within the hardware component; the modules for implementing various functions can also be considered both software programs for implementing the method and structures within the hardware component.

[0207] The above describes specific embodiments of the present invention. It should be understood that the present invention is not limited to the specific embodiments described above, and those skilled in the art may make various changes or modifications within the scope of the claims, which do not affect the essence of the present invention. The embodiments of this application and the features in the embodiments may be combined with each other in any manner unless there is a conflict.

Claims

1. A method for detecting the shape of the end of a hot-rolled steel coil online, characterized in that: include: Step S1: Denoising the measurement data; Step S2: obtaining a detection baseline based on the measurement data fitting; Step S3: merging the detection reference lines on both sides of the steel coil into a curve to obtain a fused curve set; Step S4: obtaining measurement results of the overflow edge and the pyramid shape of the steel coil end surface according to the fused curve set; In step S1: Step S1.1: The real-time speed of the strip is converted from an analog quantity to a pulse frequency. The laser ranging sensor measures the distance according to the pulse frequency, obtains the distance measurement result, and performs correction to obtain a set of data with linear correlation; The specific method for converting the real-time speed of the strip from analog to pulse frequency is as follows: s=0~D F(s) represents the frequency of analog quantity converted into pulse signal; s represents the position of the strip running range relative to the starting point; D represents the end point of the strip running range; I(s) represents the current analog value corresponding to the real-time speed of the strip, which is an analog value in the valid range of Imin~Imax; F 最大 Indicates the maximum frequency corresponding to the real-time speed of the strip; Imin represents the current analog value corresponding to the minimum real-time speed of the strip; Imax represents the current analog value corresponding to the maximum real-time speed of the strip; Imin to Imax is the valid range; The specific method of the correction is as follows: Using the fixed-distance sampling calibration method, within a distance interval Δs, the coil running speed is considered to be uniform, and the distance measurement results are uniformly corrected by equal intervals. In the Δs interval, after uniform distribution: The coordinates of the i+1th measurement point = the coordinates of the i-th measurement point + Δs / n, i = 1, 2, ..., n; n is the number of effective points of measurement; Step S1.2: Smoothing and filtering are performed on the data in the data set based on the thickness of the strip. Assuming that the thickness of the strip is h, the calculation starts from the first effective distance measurement point, and the distance measurement values are taken at intervals of h / 2. The method of taking the value is to take the average of the measured values between [-h / 2, h / 2] with this point as the center.

2. The method for detecting the shape of the end of a hot-rolled steel coil online according to claim 1, characterized in that: In step S3: Data fusion uses the feature point fitting method, which is as follows: The main characteristic points are on the same horizontal line: 2 points on the inner diameter of the steel coil and 2 points on the outer diameter of the steel coil; According to the interruptions in the measurement process, the characteristic points of the end faces of both sides of the steel coil are found respectively. According to the least square fitting principle, the fitting parameters of the two straight lines are obtained, and the two curves are merged into one curve.

3. The method for detecting the shape of the end of a hot-rolled steel coil online according to claim 1, wherein: In step S4: When the fused curve set (x i ,y i ), i = 1 to n, n is the number of effective measurement points, y i The point where >S0 is the abnormal point, thus obtaining the measurement results of the overflow edge and tower shape of the steel coil end face; S0 represents the set deviation reference value. If it exceeds the set deviation reference value, it is abnormal; if it does not exceed the set deviation reference value, it is normal. x i is the coordinate of the i-th measurement point after fusion; y i is the ranging result of the i-th measurement point after fusion.

4. A hot-rolled steel coil end shape detection system, characterized in that: include: Module M1: De-noising of measurement data; Module M2: Get the detection baseline based on the measurement data fitting; Module M3: Merge the detection reference lines on both sides of the steel coil into a curve to obtain a fused curve set; Module M4: obtaining measurement results of the overflow edge and the pyramid shape of the steel coil end surface according to the fused curve set; In the module M1: Module M1.1: Converts the real-time speed of the strip from analog to pulse frequency. The laser ranging sensor measures the distance according to the pulse frequency, obtains the distance measurement result and performs correction to obtain a set of data with linear correlation. Among them, the real-time speed of the strip is converted from analog quantity to pulse frequency. The specific system is as follows: s=0~D F(s) represents the frequency of analog quantity converted into pulse signal; s represents the position of the strip running range relative to the starting point; D represents the end point of the strip running range; I(s) represents the current analog value corresponding to the real-time speed of the strip, which is an analog value in the valid range of Imin~Imax; F 最大 Indicates the maximum frequency corresponding to the real-time speed of the strip; Imin represents the current analog value corresponding to the minimum real-time speed of the strip; Imax represents the current analog value corresponding to the maximum real-time speed of the strip; Imin to Imax is the valid range; The specific system of the correction is as follows: The system adopts fixed-distance sampling calibration. In a distance interval Δs, the running speed of the steel coil is considered to be uniform. The distance measurement results are uniformly corrected by equal intervals. In the Δs interval, after uniform distribution: The coordinates of the i+1th measurement point = the coordinates of the i-th measurement point + Δs / n, i = 1, 2, ..., n; n is the number of effective points of measurement; Module M1.2: Smoothing and filtering are performed on the data in the data set based on the strip thickness. Assuming that the strip thickness is h, the calculation starts from the first effective distance measurement point, and the distance measurement values are taken at intervals of h / 2. The value-taking system takes the average of the measured values between [-h / 2, h / 2] with this point as the center.

5. The hot rolled steel coil online end shape detection system according to claim 4, characterized in that: In the module M3: Data fusion uses the feature point fitting method, which is as follows: The main characteristic points are on the same horizontal line: 2 points on the inner diameter of the steel coil and 2 points on the outer diameter of the steel coil; According to the interruptions in the measurement process, the characteristic points of the end faces of both sides of the steel coil are found respectively. According to the least square fitting principle, the fitting parameters of the two straight lines are obtained, and the two curves are merged into one curve.

6. The hot rolled steel coil online end shape detection system according to claim 4, characterized in that: In the module M4: When the fused curve set (x i ,y i ), i = 1 to n, n is the number of effective measurement points, y i The point where >S0 is the abnormal point, thus obtaining the measurement results of the overflow edge and tower shape of the steel coil end face; S0 represents the set deviation reference value. If it exceeds the set deviation reference value, it is not abnormal, and if it does not exceed the set deviation reference value, it is normal. x i is the coordinate of the i-th measurement point after fusion; y i is the ranging result of the i-th measurement point after fusion.

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