A method for detecting the appearance quality of steel strips used for spindle conveying

Abstract

The present application relates to the technical field of steel strip detection, and specifically to a method for detecting the appearance quality of steel strips for ingot conveying, the method comprising: measuring the data sequence of the steel strip to be detected and the thickness sequence of the steel strip at each moment; performing mutation detection on the measured data sequence, combining the change distribution of the data in the local range of each element, and obtaining the mutation significance value of each element at the corresponding moment; according to the difference in the distribution of the neighborhood range data between different elements of the steel strip thickness sequence at each moment, combining the mutation significance value, obtaining the stable characteristic value of the steel strip thickness at each moment; performing modal decomposition on the stable characteristic value of the steel strip thickness at all moments, combining the fitting results of the modal components in the frequency domain and the frequency distribution, obtaining the stress influence coefficient of the steel strip; based on the stress influence coefficient of the steel strip, obtaining the appearance quality result of the steel strip to be detected. The present application aims to more comprehensively evaluate the appearance quality of the steel strip, so that the detection result is more accurate.

Description

Technical Field

[0001] The present application relates to the technical field of steel strip detection, and in particular to a method for detecting the appearance quality of a steel strip used for ingot conveying. Background Art

[0002] Because the groove of the sliding device is engaged with the steel belt, the sliding device can transfer the ingot on the steel belt. The quality of the steel belt as a guide is extremely important because it is directly related to the conveying efficiency of the ingot and the overall production effect. Therefore, the inspection of the quality of the steel belt is a key step to ensure smooth production and improve equipment efficiency.

[0003] Usually, when inspecting the quality of steel strips, the focus is on measuring the overall width and thickness, while the flatness of different surfaces of the steel strips and the random distribution of appearance defects caused by stress changes are often ignored. This practice may lead to low accuracy of appearance quality inspection results, fail to reflect the actual quality of the steel strips, and affect the conveying efficiency of the spindles. Summary of the invention

[0004] In view of the above, it is necessary to provide a method for detecting the appearance quality of steel strips used for ingot conveying to solve the above problems.

[0005] An embodiment of the present application provides a method for detecting the appearance quality of a steel strip for ingot conveying, the method comprising:

[0006] The measurement data of the measuring device on the steel strip to be tested within a preset time is combined into a measurement distance sequence; the thickness data of the measuring device at a preset number of positions at each moment on the two sides of the steel strip to be tested is combined into a steel strip thickness sequence at each moment;

[0007] Perform mutation detection on the measured distance sequence, and combine the change distribution of data in the local range of each element to obtain the mutation significance value of each element at the corresponding moment;

[0008] According to the difference in the distribution of neighborhood data between different elements of the steel strip thickness sequence at each moment, combined with the mutation significance value, the stable characteristic value of the steel strip thickness at each moment is obtained;

[0009] The modal decomposition is performed on the stable eigenvalues ​​of the steel strip thickness at all times, and the stress influence coefficient of the steel strip is obtained by combining the fitting results of the modal components in the frequency domain and the frequency distribution. Based on the stress influence coefficient of the steel strip, the appearance quality results of the steel strip to be tested are obtained.

[0010] Wherein, the step of obtaining the thickness data comprises:

[0011] The distance between the two side measurement devices of the steel strip is obtained, and the sum of the measurement data collected by the two side measurement devices at each position is calculated; and the difference between the distance and the sum is used as the thickness data of each position.

[0012] The specific process of obtaining the mutation significance value of each element at the corresponding moment is as follows:

[0013] A local window is preset with each element of the measured distance sequence as the center;

[0014] According to the mutation detection results of the data in the local window of each element of the measured distance sequence, the mutation degree of each element is obtained;

[0015] The discrete degree of the data in the local window of each element and the corresponding mutation degree are fused to obtain the mutation significance value of each element at the corresponding moment.

[0016] The mutation degree of each element is specifically the average value of the mutation test results in the local window of each element.

[0017] The step of obtaining the stable characteristic value of the steel strip thickness at each moment is as follows:

[0018] According to the similarity between the data distribution of each element in the steel strip thickness sequence at each moment and the data distribution within the neighborhood of other elements, the thickness uniformity index of each element is obtained;

[0019] Perform a trend test on the thickness uniformity index of all elements in the steel strip thickness sequence at each moment, and obtain the trend test results at each moment;

[0020] According to the trend test results at each moment and the mutation significance value, the stable characteristic value of the steel strip thickness at each moment is obtained; wherein the stable characteristic value of the steel strip thickness is negatively correlated with the absolute value of the trend test result and the mutation significance value.

[0021] The specific process of obtaining the thickness uniformity index of each element is as follows:

[0022] For the steel strip thickness sequence at each moment, a neighborhood window is preset with each element as the center; the average level of similarity between each element and the data in the neighborhood windows of all other elements is taken as the thickness uniformity index of each element.

[0023] The obtained steel strip stress influence coefficient is specifically:

[0024] Perform modal decomposition on the stable eigenvalues ​​of the steel strip thickness at all times to obtain a set number of modal components;

[0025] Obtain a fitting curve of the frequency spectrum data of each modal component, and obtain the high-frequency region and the low-frequency region of each modal component according to the frequency distribution of each modal component before fitting;

[0026] According to the fitted curves of all modal components and the shape characteristics of the corresponding high-frequency areas, the proportion of high-frequency signals of the steel strip is obtained;

[0027] The negative mapping value of the mean of the stable characteristic values ​​of the thickness of all steel strips is calculated, and the high-frequency signal proportion is fused with the negative mapping value to obtain the stress influence coefficient of the steel strip.

[0028] The process of obtaining the high-frequency region and the low-frequency region of each modal component is specifically as follows:

[0029] For each modal component in the frequency domain, obtain the average level of all frequency values ​​in each modal component, which is recorded as the split frequency value;

[0030] The frequency range in the spectrum data with a frequency greater than the split frequency value is taken as the high frequency region of each modal component, and the frequency range less than or equal to the split frequency value is taken as the low frequency region of each modal component.

[0031] The specific process of obtaining the proportion of high-frequency signals of the steel strip is as follows:

[0032] Calculate the area ratio of the high-frequency region to the low-frequency region in the fitting curve corresponding to each modal component; and take the cumulative sum of the area ratios of all modal components as the proportion of the high-frequency signal of the steel strip.

[0033] The method of obtaining the appearance quality result of the steel strip to be tested is specifically as follows:

[0034] When the normalized result of the stress influence coefficient of the steel strip is less than or equal to the preset influence threshold, the appearance quality of the steel strip is qualified; otherwise, the appearance quality of the steel strip is unqualified.

[0035] This application has at least the following beneficial effects:

[0036] The present application first obtains a measurement distance sequence based on the data collected on the steel strip, which has the beneficial effect of providing a data basis for the smooth feature analysis on the steel strip. Since the uniformity of the steel strip thickness will also affect the efficiency of the ingot transmission during the steel strip's use for ingot transmission, the thickness data at different positions on the side of the steel strip are obtained to provide a data basis for the subsequent thickness analysis of the steel strip; a mutation significance value is obtained for the measurement data on the steel strip, which has the beneficial effect of analyzing the mutation and local change characteristics of the measurement data on the steel strip, accurately reflecting the smoothness characteristics of the bottom surface of the groove of the ingot conveying sliding device, and describing the appearance quality of the steel strip; further analysis of the different positions on the side of the steel strip The thickness data of the steel strip is set to obtain the stable characteristic value of the steel strip thickness. Its beneficial effect is that the thickness characteristics at multiple positions are compared in combination with the smooth state of the steel strip, and the smooth characteristics of the other two sides of the groove of the conveying spindle sliding device are accurately reflected, which helps to improve the reliability of the detection results. Since the quality problems of the steel strip usually occur randomly and the specific positions are difficult to predict, the modal decomposition of all the stable characteristic values ​​of the steel strip thickness is carried out to construct the stress influence coefficient of the steel strip. Its beneficial effect is that the interaction between the steel strip and the contact surface of the groove is more comprehensively considered, and the appearance quality state of the steel strip can be more accurately reflected, thereby improving the accuracy of the detection results and improving the efficiency of spindle transmission. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] Figure 1 A flow chart of a method for detecting the appearance quality of a steel strip for ingot conveying provided in this application;

[0038] Figure 2 Schematic diagram of the sensor locations provided for this application;

[0039] Figure 3 A flow chart for obtaining the stable characteristic value of the steel strip thickness provided for this application;

[0040] Figure 4 A flow chart for obtaining the stress influence coefficient of the steel strip provided in this application. DETAILED DESCRIPTION

[0041] In the description of the embodiments of the present application, words such as "exemplary", "or", "for example" and the like are used to indicate examples, illustrations or descriptions. Any embodiment or design described as "exemplary" or "for example" in the embodiments of the present application should not be interpreted as being more preferred or more advantageous than other embodiments or designs. Specifically, the use of words such as "exemplary", "or", "for example" and the like is intended to present related concepts in a concrete manner.

[0042] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those commonly understood by those skilled in the art in the present application. The terms used in the specification of the present application are only for the purpose of describing specific embodiments and are not intended to limit the present application.

[0043] It should also be noted that the terms "first" and "second" in this application and its drawings are used to distinguish similar objects, rather than to describe a specific order or sequence. The method disclosed in the embodiments of the present application or the method shown in the flow chart includes one or more steps for implementing the method. Without departing from the scope of protection of this application, the execution order of multiple steps can be interchanged with each other, and some steps can also be deleted.

[0044] Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs.

[0045] This application first proposes a method for detecting the appearance quality of a steel strip for spindle conveying, which is applied in the field of steel strip detection technology. Figure 1 , the method comprises the following steps:

[0046] S1: The measurement data of the measuring device on the steel strip to be tested within a preset time are combined into a measurement distance sequence; the thickness data of the measuring device at a preset number of positions on the two sides of the steel strip to be tested at each moment are combined into a steel strip thickness sequence at each moment.

[0047] Since the groove of the sliding device is engaged with the steel belt, the sliding device can complete the transmission of the ingot on the steel belt. During the transmission process, the surface of the steel belt in contact with the bottom surface of the groove is regarded as the top of the steel belt, and the other two surfaces in contact with the groove are respectively recorded as the first side surface and the second side surface. The flatness of these contact surfaces will affect the transmission efficiency of the ingot. Based on this, the steel belt to be used for ingot transportation is measured: a laser sensor is installed directly above the steel belt, so that the laser direction is perpendicular to the top of the steel belt, and the laser falls between the two long sides of the steel belt; two line laser measuring instruments symmetrical about the steel belt are respectively aimed at the first side surface and the second side surface of the steel belt, so that the emitted linear laser is perpendicular to the first side surface and the second side surface, and the linear projections mapped on the first side surface and the second side surface are perpendicular to the long side of the contact surface; the steel belt is moved at a uniform speed along the long side direction of the contact surface. In this embodiment, the data collection time interval is 0.01 seconds, and the collection time is 30 seconds; the implementer can adjust it according to the actual situation.

[0048] The sensor location diagram is as follows: Figure 2 As shown; 1 is a laser sensor, 2 is a line laser measuring instrument, and 3 is the first side of the steel strip.

[0049] The measurement data of the laser sensor at all times are combined into a measurement distance sequence; the edge perpendicular to the bottom surface of the steel strip is evenly divided to obtain 20 positions; the implementer can adjust the number of positions measured at each moment, obtain the distance between the two line laser measuring instruments, and calculate the sum of the measurement data collected by the two line laser measuring instruments at each position; calculate the difference between the distance and the sum to obtain the thickness data of each position, and use the thickness data of all positions measured at each moment as the steel strip thickness sequence at each moment.

[0050] It should be understood that a measured distance data and a steel strip thickness sequence can be obtained at each moment; within a preset time period, a measured distance sequence and several steel strip thickness sequences can be obtained; and data at different positions on the top and side of the steel strip are measured at each moment.

[0051] S2: Perform mutation detection on the measured distance sequence, and combine the change distribution of the data within the local range of each element to obtain the mutation significance value of each element at the corresponding moment.

[0052] Since the steel strip is in direct contact with the sliding device of the conveying spindle, the smoother the surface, the more conducive it is to the stable transmission of the spindle. During the production of the steel strip, burrs may appear on the steel strip due to wear of the shear blade or uneven shear force, which may hinder the transmission. The larger and more burrs there are on the steel strip, the more obvious the mutation points of the measured distance sequence will be.

[0053] The measured distance sequence is subjected to mutation point detection to obtain the mutation test statistic at each moment; a local window is preset with each element of the measured distance sequence as the center; the average level of the mutation test statistic in the local window of each element and the discrete degree of the data in the local window are fused to obtain the mutation significance value of each element at the corresponding moment.

[0054] As an embodiment, the present application adopts the Pettitt mutation point detection algorithm to obtain the abnormal characteristics of the measured distance sequence. The input of the Pettitt algorithm is the measured distance sequence, and the output is the mutation test statistic of the distance data at each moment in the sequence. The size of the statistic value reflects the degree of mutation of the corresponding data. The larger the statistic, the greater the degree of mutation of the corresponding data. It should be noted that the Pettitt mutation point detection algorithm is an existing well-known technology, and this application does not elaborate on it; in addition, the implementer may also use other mutation point detection algorithms to obtain the mutation test statistic of each element in the sequence, and this application does not limit this.

[0055] Furthermore, if a tiny burr appears only at a certain point in a local area on the steel belt, the burr defect will hardly affect the conveying process; however, if there are more burr defects in the local area, the vibration generated by the conveying friction will be greater. Based on this, the distance data on the steel belt in a short period of time is analyzed: with each element of the measured distance sequence as the center, the window size is set to If there is missing data in the window, it is filled by mirror filling; in addition, the implementer can adjust the size of the local window according to the actual situation.

[0056] For the local window of the ith element in the measurement distance sequence, first calculate the coefficient of variation of all data in the local window of the ith element, denoted as ; The larger the coefficient of variation, the greater the degree of dispersion of the local area of ​​the element; in other embodiments, the standard deviation can be used instead of the coefficient of variation. Then, the mean of the mutation test statistic corresponding to all data in the local window of the i-th element is calculated, which is recorded as , the larger the mean of the mutation test statistic, the more obvious the abnormal burr characteristics of the local area of ​​the element; in other embodiments, the median can be used instead of the mean. In this embodiment, the two variables are fused by multiplication, that is, As the mutation significance value of the i-th element at the corresponding moment, it is recorded as The larger the mutation significance value is, the less smooth the position on the steel strip measured at that moment is, and there may be abnormal jitter when the spindle is transported through this position.

[0057] S3: According to the difference in the distribution of neighborhood data between different elements of the steel strip thickness sequence at each moment, combined with the mutation significance value, the stable characteristic value of the steel strip thickness at each moment is obtained.

[0058] In addition to the smoothness of the steel belt having a significant impact on the stability of the conveying process, irregular defects on both sides of the steel belt will also hinder the smooth conveying of the ingot. These surface defects are mainly manifested as uneven thickness, which will lead to unbalanced forces between the ingot conveying fixture and the steel belt, and then cause the fixture to shake. Based on this feature, the uniformity characteristics of the steel belt thickness are analyzed below.

[0059] For the steel strip thickness sequence at each moment, a neighborhood window is preset with each element as the center; the thickness uniformity index of each element is obtained according to the similarity between the neighborhood window of each element and the data in the neighborhood windows of other elements; a trend test is performed on the thickness uniformity index of all elements in the steel strip thickness sequence at each moment to obtain the trend test result at each moment; based on the trend test result at each moment and the mutation significance value, the stable characteristic value of the steel strip thickness at each moment is obtained; wherein, the stable characteristic value of the steel strip thickness is negatively correlated with the absolute value of the trend test result and the mutation significance value.

[0060] As an embodiment, firstly, the uniform characteristics of the steel strip thickness at each position at each moment are analyzed. For the steel strip thickness sequence at the ith moment, each element is taken as the center, and a local range with a left and right data volume of 7 is set as the neighborhood window of each element. If there is missing data in the neighborhood, it is filled by mirror filling; in addition, the implementer can adjust the size of the neighborhood window by himself. Calculate the Jaccard similarity coefficient of the data in the neighborhood window between the jth element at the ith moment and all other elements, and take the average of the Jaccard similarity coefficients of the jth element at the ith moment and all other elements as the thickness uniformity index of the jth element, denoted as , the income The larger it is, the closer the steel strip thickness data at that moment is.

[0061] The thickness uniformity index reflects the thickness distribution characteristics of the steel strip at each moment. However, the thickness at different moments and the smoothness of the two sides can affect the spindle conveyance at the same time. For the i-th moment, the thickness uniformity index of all positions is composed of the thickness uniformity sequence and recorded as Under ideal conditions, the distribution of the uniformity data of the steel strip thickness is stable. The Mann-Kendall algorithm is used to obtain the trend characteristics of the thickness uniformity sequence, and the output is the trend test result, which is recorded as .

[0062] Furthermore, the stable characteristic value of the steel strip thickness at the i-th moment is analyzed, and the specific calculation formula is as follows: ; In the formula, represents the stable characteristic value of the steel strip thickness at the i-th moment, represents the trend test result at the i-th moment, Represents the mutation significance value corresponding to the i-th moment. Among them, the flow chart of obtaining the stable characteristic value of steel strip thickness is as follows: Figure 3 shown.

[0063] It should be understood that the smaller the absolute value of the trend test result, the more uniform the distribution of the steel strip thickness data measured at that moment; the smaller the mutation significance value, the less the distribution of burrs on the steel strip measured at that moment. At this time, the larger the stable characteristic value of the steel strip thickness, the smoother the overall contact surface between the steel strip and the sliding device measured at that moment.

[0064] S4: Perform modal decomposition on the stable eigenvalues ​​of the steel strip thickness at all times, and obtain the stress influence coefficient of the steel strip by combining the fitting results of the modal components in the frequency domain and the frequency distribution; based on the stress influence coefficient of the steel strip, obtain the appearance quality results of the steel strip to be tested.

[0065] In addition, the fixture for conveying the ingot needs to maintain stability during the transmission process using the sliding device. Since the distribution of surface defects in the process of steel strip production is highly random, the stable characteristic value of the steel strip thickness may have different frequency characteristics. For example, due to stress changes on the steel strip surface, the difference in defect characteristics between different measurement positions is large, which causes random fluctuations in the stable characteristic value of the steel strip thickness. As the difference in stress changes increases, the frequency of fluctuations in the stable characteristic value of the steel strip thickness increases. The sequence composed of the stable characteristic values ​​of the steel strip thickness at all times is recorded as a smooth consistency sequence, and the surface state of the steel strip is further obtained based on the frequency characteristics of the smooth consistency sequence.

[0066] The sequence composed of the stable characteristic values ​​of the steel strip thickness at all moments is recorded as a smooth consistency sequence; the smooth consistency sequence is modally decomposed to obtain a set number of modal components; the frequency spectrum data of each modal component is curve fitted, and the high-frequency area and low-frequency area of ​​each modal component are obtained according to the frequency distribution of each modal component before fitting; the proportion of high-frequency signals of the steel strip is obtained according to the shape characteristics of the curves after fitting of all modal components and the corresponding high-frequency areas.

[0067] The negative mapping value of the element mean of the smooth consistency sequence is calculated, and the high-frequency signal proportion is fused with the negative mapping value to obtain the stress influence coefficient of the steel strip.

[0068] As an embodiment, the empirical mode decomposition algorithm (EMD) is first used to obtain the various modal components of the smooth consistency sequence. The number of components output in this embodiment is 4; the implementer can adjust it by himself. Each modal component represents a different frequency characteristic of the smooth consistency sequence. Discrete Fourier transform is performed on each modal component to obtain spectrum data, wherein the spectrum data includes frequency values ​​and their corresponding amplitude values. The spectrum data is firstly subjected to curve fitting using the least squares method. Taking the spectrum data corresponding to the kth modal component as an example, in order to extract its high-frequency signal, the median of all frequency values ​​in the spectrum data is used as the split frequency value, and the frequency range greater than the median is defined as the high-frequency region, and the frequency range less than the median is defined as the low-frequency region. The more signals in the high-frequency region, the more surface defects of the steel strip are distributed; in other embodiments, the split frequency value can also be the average value of all frequencies.

[0069] The area of ​​the high-frequency region and the low-frequency region in the fitting curve corresponding to each modal component is calculated by the integration method, and the ratio of the area of ​​the high-frequency region to the area of ​​the low-frequency region is calculated. The cumulative sum of the ratios of all modal components is taken as the proportion of the high-frequency signal of the steel strip, which is recorded as Therefore, the stress influence coefficient of the steel strip is calculated as follows: ; In the formula, represents the stress influence coefficient of the steel strip, is the proportion of high-frequency signals of steel strip, is the element mean of the smooth consistency sequence. Among them, the flow chart of obtaining the stress influence coefficient of the steel strip is as follows: Figure 4 shown.

[0070] It should be understood that the greater the proportion of the obtained high-frequency signal, the greater the degree of change in the appearance of the steel strip, that is, there is a large difference in the smoothness state between the regions. The smaller the mean of the smooth consistency sequence, the lower the overall smoothness of the steel strip measured at that moment. The larger the obtained steel strip stress influence coefficient, the more obvious the defects in the appearance of the steel strip.

[0071] In order to better quantitatively evaluate the quality of the steel strip, the stress influence coefficient of the steel strip is normalized. Normalize, where is the normalized result of the stress influence coefficient of the steel strip, is an exponential function with a natural constant as its base.

[0072] When the normalized result of the stress influence coefficient of the steel strip is less than or equal to the preset influence threshold, the appearance quality of the steel strip is qualified; otherwise, the appearance quality of the steel strip is unqualified. In this implementation, the influence threshold is 0.5; the implementer can set it by himself.

[0073] The embodiment of the present application provides a method for detecting the appearance quality of a steel strip used for ingot conveying, the method comprising: first, obtaining a measurement distance sequence based on data collected on the steel strip, which has the beneficial effect of providing a data basis for analyzing the smoothness characteristics on the steel strip. Since the uniformity of the thickness of the steel strip will also affect the efficiency of the ingot transmission during the steel strip is used for ingot transmission, the thickness data of different positions on the side of the steel strip are obtained to provide a data basis for the subsequent thickness analysis of the steel strip; for the measurement data on the steel strip, a mutation significance value is obtained, which has the beneficial effect of analyzing the mutation and local change characteristics of the measurement data on the steel strip, accurately reflecting the smoothness characteristics of the bottom surface of the groove of the conveying ingot sliding device, and describing the appearance of the steel strip. The thickness data at different positions on the side of the steel strip are further analyzed to obtain the stable characteristic value of the steel strip thickness. The beneficial effect is that the thickness characteristics at multiple positions are compared in combination with the smooth state of the steel strip, and the smooth characteristics of the other two sides of the groove of the conveying spindle sliding device are accurately reflected, which helps to improve the reliability of the detection results. Since the quality problems of the steel strip usually occur randomly and the specific positions are difficult to predict, the modal decomposition of all the stable characteristic values ​​of the steel strip thickness is carried out to construct the stress influence coefficient of the steel strip. The beneficial effect is that the interaction between the steel strip and the groove contact surface is more comprehensively considered, and the appearance quality state of the steel strip can be more accurately reflected, thereby improving the accuracy of the detection results and improving the efficiency of spindle transmission.

[0074] The flowchart and block diagram in the accompanying drawings show the possible architecture, function and operation of the system, method and computer program product according to the embodiment of the present application. In this regard, each box in the flowchart or block diagram can represent a module, a program segment or a part of the code, and the module, the program segment or a part of the code contains one or more executable instructions for realizing the specified logical function. In some alternative implementations, the function marked in the box can also occur in a different order from the order marked in the accompanying drawings. For example, two continuous boxes can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, which can depend on the functions involved. In the description corresponding to the flowchart and the block diagram in the accompanying drawings, the operations or steps corresponding to different boxes can also occur in a different order from the order disclosed in the description, and sometimes there is no specific order between different operations or steps. For example, two continuous operations or steps can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, which can depend on the functions involved. Each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, may be implemented by a dedicated hardware-based system that performs the specified functions or actions, or may be implemented by a combination of dedicated hardware and computer instructions.

[0075] The above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. These modifications or replacements do not deviate the essence of the corresponding technical solutions from the scope of the technical solutions of the embodiments of the present application, and should all be included in the protection scope of the present application.

Claims

1. A method for detecting the appearance quality of a steel strip used for spindle conveying, characterized in that: The method comprises the following steps: The measurement data of the measuring device on the steel strip to be tested within a preset time is combined into a measurement distance sequence; the thickness data of the measuring device at a preset number of positions at each moment on the two sides of the steel strip to be tested is combined into a steel strip thickness sequence at each moment; Perform mutation detection on the measured distance sequence, and combine the change distribution of data in the local range of each element to obtain the mutation significance value of each element at the corresponding moment; According to the difference in the distribution of neighborhood data between different elements of the steel strip thickness sequence at each moment, combined with the mutation significance value, the stable characteristic value of the steel strip thickness at each moment is obtained; The modal decomposition is performed on the stable eigenvalues ​​of the steel strip thickness at all times, and the stress influence coefficient of the steel strip is obtained by combining the fitting results of the modal components in the frequency domain and the frequency distribution. Based on the stress influence coefficient of the steel strip, the appearance quality results of the steel strip to be tested are obtained.

2. A method for detecting the appearance quality of a steel strip for spindle conveying as claimed in claim 1, characterized in that: The step of obtaining the thickness data comprises: The distance between the two side measurement devices of the steel strip is obtained, and the sum of the measurement data collected by the two side measurement devices at each position is calculated; and the difference between the distance and the sum is used as the thickness data of each position.

3. A method for detecting the appearance quality of a steel strip for spindle conveying as claimed in claim 1, characterized in that: The specific process of obtaining the mutation significance value of each element at the corresponding moment is: A local window is preset with each element of the measured distance sequence as the center; According to the mutation detection results of the data in the local window of each element of the measured distance sequence, the mutation degree of each element is obtained; The discrete degree of the data in the local window of each element and the corresponding mutation degree are fused to obtain the mutation significance value of each element at the corresponding moment.

4. A method for detecting the appearance quality of a steel strip for spindle conveying as claimed in claim 3, characterized in that: The mutation degree of each element is specifically the average value of the mutation test results in the local window of each element.

5. A method for detecting the appearance quality of a steel strip for spindle conveying as claimed in claim 1, characterized in that: The steps of obtaining the stable characteristic value of the steel strip thickness at each moment are: According to the similarity between the data distribution of each element in the steel strip thickness sequence at each moment and the data distribution within the neighborhood of other elements, the thickness uniformity index of each element is obtained; Perform a trend test on the thickness uniformity index of all elements in the steel strip thickness sequence at each moment, and obtain the trend test results at each moment; According to the trend test results at each moment and the mutation significance value, the stable characteristic value of the steel strip thickness at each moment is obtained; wherein the stable characteristic value of the steel strip thickness is negatively correlated with the absolute value of the trend test result and the mutation significance value.

6. A method for detecting the appearance quality of a steel strip for spindle conveying as claimed in claim 5, characterized in that: The specific process of obtaining the thickness uniformity index of each element is as follows: For the steel strip thickness sequence at each moment, a neighborhood window is preset with each element as the center; the average level of similarity between each element and the data in the neighborhood windows of all other elements is taken as the thickness uniformity index of each element.

7. A method for detecting the appearance quality of a steel strip for spindle conveying as claimed in claim 1, characterized in that: The obtained steel strip stress influence coefficient is specifically: Perform modal decomposition on the stable eigenvalues ​​of the steel strip thickness at all times to obtain a set number of modal components; Obtain a fitting curve of the frequency spectrum data of each modal component, and obtain the high-frequency region and the low-frequency region of each modal component according to the frequency distribution of each modal component before fitting; According to the fitted curves of all modal components and the shape characteristics of the corresponding high-frequency areas, the proportion of high-frequency signals of the steel strip is obtained; The negative mapping value of the mean of the stable characteristic values ​​of the thickness of all steel strips is calculated, and the high-frequency signal proportion is fused with the negative mapping value to obtain the stress influence coefficient of the steel strip.

8. A method for detecting the appearance quality of a steel strip for spindle conveying as claimed in claim 7, characterized in that: The process of obtaining the high-frequency region and the low-frequency region of each modal component is specifically as follows: For each modal component in the frequency domain, obtain the average level of all frequency values ​​in each modal component, which is recorded as the split frequency value; The frequency range in the spectrum data with a frequency greater than the split frequency value is taken as the high frequency region of each modal component, and the frequency range less than or equal to the split frequency value is taken as the low frequency region of each modal component.

9. A method for detecting the appearance quality of a steel strip for spindle conveying as claimed in claim 7, characterized in that: The specific process of obtaining the proportion of high-frequency signals of the steel strip is as follows: Calculate the area ratio of the high-frequency region to the low-frequency region in the fitting curve corresponding to each modal component; and take the cumulative sum of the area ratios of all modal components as the proportion of the high-frequency signal of the steel strip.

10. A method for detecting the appearance quality of a steel strip for spindle conveying as claimed in claim 1, characterized in that: The obtaining of the appearance quality result of the steel strip to be tested is specifically as follows: When the normalized result of the stress influence coefficient of the steel strip is less than or equal to the preset influence threshold, the appearance quality of the steel strip is qualified; otherwise, the appearance quality of the steel strip is unqualified.

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