Method and device for measuring the outside diameter deviation of a precision seamless steel tube

Abstract

The present application relates to the technical field of outer diameter measurement, in particular to a precision seamless steel pipe outer diameter deviation measurement method and device. The method first analyzes the vibration deviation between the vibration data and the outer diameter data of the precision seamless steel pipe to obtain an abnormal deviation period; according to the difference between the vibration data corresponding to the abnormal deviation period and the previous normal period, and the difference between the outer diameter data corresponding to the abnormal deviation period and the previous normal period, a normal segmentation coefficient of the abnormal deviation period as a segmentation period is determined; the proportion of the time length of the abnormal change of the outer diameter data in the abnormal deviation period is analyzed to determine the control abnormal coefficient of the abnormal deviation period; the data abnormal value of the abnormal deviation period is determined in combination with the normal segmentation coefficient and the control abnormal coefficient; when the data abnormal value exceeds the normal range, the outer diameter data under the corresponding abnormal deviation period is re-measured. The present application improves the accuracy of the outer diameter deviation measurement of the precision seamless steel pipe.

Description

Technical Field

[0001] This invention relates to the field of outer diameter measurement technology, specifically to a method and apparatus for measuring the outer diameter deviation of a precision seamless steel pipe. Background Technology

[0002] Precision seamless steel pipes are widely used in precision industries such as oil and gas transportation. Therefore, the requirements for pipelines made of seamless steel pipes are more stringent. In pipeline welding, if the precision seamless steel pipes produced have unqualified diameters or roundness, misalignment will occur when welding two steel pipes. If unqualified steel pipes are forcibly welded together, the steel pipes will exert tension on each other. Over time, this will significantly reduce the mechanical properties of the weld between the two steel pipes, eventually leading to cracking of the weld and creating serious safety hazards. Therefore, improving the accuracy of outer diameter testing of precision seamless steel pipes is crucial.

[0003] Currently, the common method for measuring the outer diameter of precision seamless steel pipes is the oblique laser triangulation method. This method involves a laser probe shining a laser beam onto the steel pipe, which then reflects the laser beam and shines onto a photoelectric position sensor (PSD). As the distance to the PSD increases, the resistance changes accordingly, which in turn causes a change in current. By analyzing the magnitude of the current, the position of the reflected laser beam on the PSD can be obtained. By measuring the distance between the laser probe, the steel pipe surface, and the PSD, and analyzing the change in distance, the outer diameter of the steel pipe can be obtained.

[0004] When measuring the outer diameter, the steel pipe needs to be transported, rotated, and held by rollers. During this process, due to the large length and diameter of the steel pipe, multiple rollers are required to support it. Due to the unevenness between the rollers and the redundancy of the gears in the roller drive process, the steel pipe vibrates in some positions, causing high-frequency fluctuations when the reflected light beam hits the PSD. These fluctuations affect the length of the measured light path, which in turn leads to errors when measuring the outer diameter of precision seamless steel pipes. Summary of the Invention

[0005] To address the technical problem of errors in measuring the outer diameter of steel pipes caused by unevenness of the rollers during transport and rotation, this invention aims to provide a method and apparatus for measuring the outer diameter deviation of precision seamless steel pipes. The specific technical solution adopted is as follows:

[0006] In a first aspect, embodiments of the present invention provide a method for measuring the outer diameter deviation of a precision seamless steel pipe, the method comprising:

[0007] Obtain vibration and outer diameter data of precision seamless steel pipes at each measurement point;

[0008] Analyze the vibration deviation between vibration data and outer diameter data to identify the periods of abnormal deviation.

[0009] Based on the differences in vibration data and outer diameter data between the abnormal deviation period and the previous normal period, the abnormal deviation period is determined as the normal segmentation coefficient of the segmentation period.

[0010] Analyze the percentage of time during which the inner and outer diameter data show abnormal changes during periods of abnormal deviation, and determine the control abnormality coefficient for these periods.

[0011] By combining the normal segmentation coefficient and the control anomaly coefficient, the abnormal data values ​​for the abnormal deviation period are determined; when the abnormal data values ​​exceed the normal range, the outer diameter data for the corresponding abnormal deviation period are remeasured.

[0012] Furthermore, the vibration deviation between the analyzed vibration data and the outer diameter data is used to determine the abnormal deviation time periods, including:

[0013] Analyze the deviation between the frequency spectra of vibration data and outer diameter data at the same time to determine the frequency variation coefficient;

[0014] The abnormal deviation period is defined as the continuous time period corresponding to the frequency variation coefficient that is greater than the preset variation threshold.

[0015] Furthermore, the analysis of the deviation between the frequency spectra of the vibration data and the outer diameter data at the same moment, and the determination of the frequency variation coefficient, includes:

[0016] Use any time as the target time and any frequency as the target frequency;

[0017] The difference in amplitude of the target frequency between the spectrum diagram of the vibration data at the target time and the spectrum diagram of the outer diameter data is calculated and used as the amplitude measurement difference of the target frequency.

[0018] The contribution weight corresponding to the frequency is determined based on the magnitude of the frequency.

[0019] For the target frequency, a single variation coefficient of the target frequency is obtained by combining the amplitude measurement difference and the contribution weight.

[0020] By combining the single variation coefficients of all frequencies at the target time, the frequency variation coefficient at the target time is obtained.

[0021] Further, determining the normal segmentation coefficient of the segmented time period based on the difference in vibration data corresponding to the abnormal deviation period and the previous normal period, and the difference in outer diameter data corresponding to the abnormal deviation period and the previous normal period, includes:

[0022] Analyze the differences in vibration data between the abnormal deviation period and the previous normal period to determine the amplitude deviation coefficient;

[0023] Analyze the differences in outer diameter data between the abnormal deviation period and the previous normal period to determine the outer diameter deviation coefficient;

[0024] By combining the amplitude deviation coefficient and the outer diameter deviation coefficient, the abnormal deviation period is determined as the normal segmentation coefficient of the segmentation period; wherein, both the amplitude deviation coefficient and the outer diameter deviation coefficient are positively correlated with the normal segmentation coefficient.

[0025] Furthermore, the analysis of the difference in outer diameter data between the abnormal deviation period and the previous normal period, and the determination of the outer diameter deviation coefficient, includes:

[0026] Obtain the maximum amplitude value among all frequencies in the spectrum of the outer diameter data corresponding to the abnormal deviation period, and use the frequency corresponding to the maximum amplitude value as the benchmark frequency;

[0027] The difference between the maximum amplitude corresponding to the abnormal deviation period and the amplitude of the benchmark frequency in the spectrum diagram of the outer diameter data corresponding to the previous normal period is used as the outer diameter deviation coefficient.

[0028] Furthermore, the analysis of the difference between the vibration data corresponding to the abnormal deviation period and the previous normal period, and the determination of the amplitude deviation coefficient, includes:

[0029] For any spectrum graph, the amplitude of all frequencies in the spectrum graph is normalized. The normalized amplitude value is used as the weight of the corresponding frequency. The frequency weight is summed in a weighted manner to obtain the frequency weighted mean of the spectrum graph.

[0030] Using the frequency-weighted mean of the vibration data spectrum during the abnormal deviation period as the numerator and the frequency-weighted mean of the outer diameter data during the abnormal deviation period as the denominator, the same reference for the abnormal deviation period is obtained.

[0031] Determine the reference from the previous normal period;

[0032] The difference between the abnormal deviation period and the previous normal period is used as the amplitude deviation coefficient.

[0033] Furthermore, the analysis of the percentage of time during which the inner and outer diameter data showed abnormal changes during the abnormal deviation period, and the determination of the control anomaly coefficient for the abnormal deviation period, includes:

[0034] Determine the second derivatives of the inner and outer diameter data at different times during the period of abnormal deviation;

[0035] The moment when the second derivative is greater than 0 is defined as the moment when the outer diameter data shows abnormal changes;

[0036] The percentage of the cumulative duration of times when the outer diameter data shows abnormal changes is used as the control abnormality coefficient for abnormal deviation periods.

[0037] Furthermore, the step of combining the normal segmentation coefficient and the control anomaly coefficient to determine the data anomaly values ​​during the abnormal deviation period includes:

[0038] By performing negative correlation mapping on the normal segmentation coefficients, abnormal segmentation coefficients are obtained;

[0039] By combining the anomaly segmentation coefficient and the control anomaly coefficient, the abnormal data values ​​during the abnormal deviation period are determined; wherein, both the anomaly segmentation coefficient and the control anomaly coefficient are positively correlated with the abnormal data values.

[0040] Furthermore, determining the data anomaly values ​​during the abnormal deviation period by combining the anomaly segmentation coefficient and the control anomaly coefficient includes:

[0041] The product of the anomaly segmentation coefficient and the control anomaly coefficient is taken as the data anomaly value during the anomaly deviation period.

[0042] Secondly, a device for measuring the outer diameter deviation of a precision seamless steel pipe is provided, the device comprising the following modules:

[0043] The initial measurement module is used to acquire vibration data and outer diameter data of the steel pipe at each measurement point;

[0044] The initial time period determination module is used to analyze the vibration deviation between vibration data and outer diameter data to obtain the time period of abnormal deviation;

[0045] The first analysis module is used to determine the normal segmentation coefficient of the abnormal deviation period as the segmentation period based on the difference between the vibration data corresponding to the previous normal period and the difference between the outer diameter data corresponding to the abnormal deviation period and the previous normal period.

[0046] The second analysis module is used to analyze the percentage of time during which the inner and outer diameter data show abnormal changes during the abnormal deviation period, and to determine the control abnormality coefficient for the abnormal deviation period.

[0047] The data remeasurement module is used to determine the abnormal data values ​​during abnormal deviation periods by combining the normal segmentation coefficient and the control anomaly coefficient; when the abnormal data values ​​exceed the normal range, the outer diameter data under the corresponding abnormal deviation period is remeasured.

[0048] Thirdly, embodiments of the present invention provide an electronic device, including a memory and a processor, wherein the memory stores executable code, and when the processor executes the executable code, it implements the various possible implementations of the first aspect.

[0049] Fourthly, embodiments of the present invention provide a computer program product comprising: computer program code, which, when executed on a computer, causes the computer to perform the method described in the first aspect or any possible implementation thereof.

[0050] Fifthly, embodiments of the present invention provide a computer-readable storage medium having a computer program stored thereon, which, when executed in a computer, causes the computer to perform the various possible implementations of the first aspect.

[0051] The embodiments of the present invention have at least the following beneficial effects:

[0052] This invention identifies abnormal deviation periods not caused by pipe vibration by analyzing the deviations between vibration and outer diameter data at different measurement points of the steel pipe. It then determines a normal segmentation coefficient by analyzing the differences in vibration and outer diameter data between abnormal deviation periods and normal periods. A larger normal segmentation coefficient indicates a segmented period corresponding to the abnormal deviation, rather than an abnormal period caused by the steel pipe itself. By analyzing the proportion of time during which the inner and outer diameter data show abnormal changes during abnormal deviation periods, a control anomaly coefficient is determined for these periods. Finally, combining the normal segmentation coefficient and the control anomaly coefficient, the abnormal data values ​​for the abnormal deviation periods are determined. When the abnormal data values ​​exceed the normal range, the outer diameter data for the corresponding abnormal deviation period is remeasured. This invention remeasures abnormal deviation periods that may be caused by fluctuations, avoiding errors that can easily occur in single outer diameter measurements due to pipe vibration, thus improving the accuracy of outer diameter deviation measurements for precision seamless steel pipes. Attached Figure Description

[0053] To more clearly illustrate the technical solutions and advantages in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0054] Figure 1 A flowchart illustrating a method for measuring the outer diameter deviation of a precision seamless steel pipe, as provided in one embodiment of the present invention;

[0055] Figure 2 This is a schematic diagram of a precision seamless steel pipe outer diameter deviation measuring device provided in one embodiment of the present invention. Detailed Implementation

[0056] To further illustrate the technical means and effects of the present invention in achieving its intended purpose, the following detailed description, in conjunction with the accompanying drawings and preferred embodiments, details the specific implementation, structure, features, and effects of a precision seamless steel pipe outer diameter deviation measurement method and apparatus proposed according to the present invention.

[0057] In the following description, different "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. Furthermore, specific features, structures, or characteristics in one or more embodiments may be combined in any suitable form.

[0058] In the description of the embodiments of the present invention, unless otherwise stated, " / " means "or". For example, A / B can mean A or B. The "and / or" in the text is merely a description of the relationship between related objects, indicating that there can be three relationships. For example, A and / or B can mean: A exists alone, A and B exist simultaneously, and B exists alone. In addition, in the description of the embodiments of the present invention, "multiple" means two or more.

[0059] Hereinafter, the terms "first" and "second" are used for descriptive purposes only and should not be construed as implying or suggesting relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature.

[0060] Unless otherwise defined, 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 invention pertains.

[0061] The embodiments of the present invention will now be described with reference to the accompanying drawings. Those skilled in the art will recognize that, with technological advancements and the emergence of new scenarios, the technical solutions provided by the embodiments of the present invention are also applicable to similar technical problems.

[0062] This invention provides a specific implementation method and device for measuring the outer diameter deviation of precision seamless steel pipes. This method is applicable to steel pipe measurement scenarios. In this scenario, an outer diameter measuring device is deployed. This device is a laser displacement sensor, which includes a laser probe and a PSD (Power Distribution Detector). When measuring the outer diameter of a precision seamless steel pipe, a modular robotic arm aligns its rotation center with the center of the pipe. A pulsed laser is emitted onto the surface of the pipe through the laser probe and received by the PSD, thus obtaining the laser path.

[0063] The following description, in conjunction with the accompanying drawings, details the specific scheme of the method and apparatus for measuring the outer diameter deviation of a precision seamless steel pipe provided by the present invention.

[0064] Please see Figure 1The diagram illustrates a flowchart of a method for measuring the outer diameter deviation of a precision seamless steel pipe according to an embodiment of the present invention. The method includes the following steps:

[0065] Step S100: Obtain vibration data and outer diameter data of the precision seamless steel pipe at each measurement point.

[0066] When the steel pipe is conveyed to the measuring device by rollers, measuring points are set at fixed intervals on the precision seamless steel pipe. The laser probe of the measuring device is arranged above the steel pipe, and the laser emitted by the laser probe is vertically irradiated on the steel pipe.

[0067] First, the outer diameter of the precision seamless steel pipe at each measurement point is measured using the oblique laser triangulation method. This outer diameter is the outer radius of the precision seamless steel pipe. The specific measurement process is as follows: During the measurement, the roller drives the steel pipe to rotate 360 ​​degrees, and the laser probe emits a high-frequency laser pulse towards the steel pipe. The pulse frequency is selected as 500kHz. The interface of the steel pipe surface is constructed using the position where the laser irradiates the steel pipe surface as the tangent point. The laser reflection angle is obtained by measuring the incident angle of the laser, and a PSD photosensitive device is installed on the path of the reflection angle. Ideally, the tangent plane is constructed using the standard radius position of the steel pipe as the tangent point. When the reflected laser path passes through the plane where the laser probe is located, the position where the reflected laser path passes through is taken as the center of the PSD photosensitive device.

[0068] The outer diameter data measured at each sampling time is used to construct a time series sequence, resulting in an outer diameter data sequence. It should be noted that each sampling time corresponds to a specific measurement point. For example, if there are 200 measurement points on the steel pipe, each sampling time corresponds to one measurement point, and the corresponding outer diameter data sequence contains 200 outer diameter data points.

[0069] Simultaneously, vibration sensors are installed on the roller module at the measurement point, ensuring that the measurement frequency of the vibration sensors matches the laser pulse frequency. This yields a sequence of vibration data at all sampling times, denoted as the vibration data sequence. It should be noted that the vibration data collected by the vibration sensors is in the form of vibration displacement.

[0070] Step S200: Analyze the vibration deviation between the vibration data and the outer diameter data to obtain the time period of abnormal deviation.

[0071] Because the steel pipe is hollow and has a relatively long length, it may vibrate during the movement of the rollers, which can affect the accuracy of the outer diameter measurement. There are two reasons for the vibration of the steel pipe: firstly, the linkage between multiple rollers causes the steel pipe to deform and vibrate; secondly, the hollow effect of the steel pipe causes it to resonate.

[0072] Normally, the outer diameter of a steel pipe is measured and evaluated using oblique laser triangulation. However, in practice, if the steel pipe itself vibrates, this vibration will affect the laser's trajectory. Since the steel pipe is annular with a curved surface, even a small vibration can cause deviations in the cross-section of the laser beam irradiated on the pipe, resulting in high-frequency variations in the reflected path onto the PSD (Polarization and Deposition of Surface) surface. That is, if the steel pipe vibrates, the vibration will closely approximate the change in the outer diameter measured by the PSD. Therefore, in this embodiment of the invention, the deviation between the vibration data and the outer diameter data of the steel pipe is analyzed to identify periods of abnormal deviation. These periods of abnormal deviation constitute a time interval.

[0073] First, a time-series window is constructed. For the i-th sampling time, the time-series window is selected before the i-th sampling time, that is, the time within the time-series window is the 100 sampling times before the i-th sampling time. The outer diameter data subsequence corresponding to the i-th sampling time is obtained, and the Fourier transform of the outer diameter data subsequence is performed to obtain the corresponding spectrum. This spectrum is the spectrum of the outer diameter data at the i-th sampling time.

[0074] Similarly, the vibration data subsequence within the time window corresponding to the i-th sampling time is obtained, and a Fourier transform is performed on the vibration data subsequence to obtain the corresponding spectrum. This spectrum is the spectrum corresponding to the vibration data at the i-th sampling time. In this embodiment of the invention, the length of the time window is set to 100, that is, the time window contains 100 sampling times.

[0075] The spectrum diagram can reflect the fluctuation. If the fluctuation in the outer diameter data of the steel pipe is due to laser vibration caused by the vibration of the steel pipe, resulting in positional fluctuations when it is irradiated on the PSD, then the difference between the spectrum diagrams corresponding to the normal vibration data and the outer diameter data will be smaller. If the difference between the two spectrum diagrams is larger, it indicates that the difference is not caused by fluctuation. If the steel pipe itself does not have a change in vibration frequency, but the radius of the steel pipe has changed significantly, it indicates that the outer diameter of the steel pipe may be abnormal.

[0076] Therefore, further analysis is conducted on the deviation between the frequency spectra of the vibration data and the outer diameter data at the same moment to determine the frequency variation coefficient. More specifically:

[0077] Use any time as the target time and any frequency as the target frequency;

[0078] The difference in amplitude of the target frequency between the spectrum graph corresponding to the vibration data and the spectrum graph corresponding to the outer diameter data at the target time is calculated as the amplitude measurement difference of the target frequency at the target time. It should be noted that the frequency interval between the two spectrum graphs remains consistent, the horizontal axis of the spectrum graph represents the frequency, and the horizontal axis of the spectrum graph is arranged in ascending order of frequency.

[0079] Based on the frequency, the contribution weight corresponding to the frequency is determined. This contribution weight is a normalized value of the frequency. The higher the frequency, the closer the contribution weight is to 1, and vice versa.

[0080] For the target frequency, a single variation coefficient of the target frequency is obtained by combining the amplitude measurement difference and the contribution weight.

[0081] By combining the single variation coefficients of all frequencies at the target time, the frequency variation coefficient at the target time is obtained.

[0082] Taking the i-th time as the target time and the j-th frequency as the target frequency, the frequency variation coefficient at the i-th time... The calculation method is as follows:

[0083] ;

[0084] in, Let be the union of the frequencies in the spectrum of the outer diameter data subsequence at time i and the spectrum of the vibration data subsequence; Let be the amplitude of the j-th frequency in the spectrum of the outer diameter data subsequence. Let be the amplitude of the j-th frequency in the spectrum of the amplitude data subsequence. The contribution weight for the j-th frequency; It is the single variation coefficient of the j-th spectrum at the target time; Let be the amplitude measurement difference of the j-th spectrum at the target time.

[0085] The logic for obtaining contribution weights is as follows: In the spectrum diagram, high frequency represents the frequency of rapid fluctuations, and low frequency represents the trend of data. Both vibration and the position change of the laser on the PSD are high-frequency changes. In the low-frequency data, since there is no rigid connection between the vibration of the roller and the vibration of the steel pipe, there is a certain difference in the vibration trend. Therefore, it is necessary to reduce the difference in low-frequency data.

[0086] Furthermore, after obtaining the frequency variation coefficient at each time step, a sequence of frequency variation coefficients at each time step is constructed.

[0087] When the variations in the vibration data subsequence and the outer diameter data subsequence are not equal, it indicates that there may be an outer diameter deviation, which may lead to differences in PSD reflection.

[0088] Therefore, the mean of the frequency variation coefficient sequence is obtained, and this mean is used as a preset variation threshold. The time corresponding to the frequency variation coefficient that is greater than the preset variation threshold is taken as the abnormal deviation time. The abnormal deviation time period is composed of consecutive abnormal deviation times.

[0089] Step S300: Based on the difference between the vibration data corresponding to the abnormal deviation period and the previous normal period, and the difference between the outer diameter data corresponding to the abnormal deviation period and the previous normal period, determine the abnormal deviation period as the normal segmentation coefficient of the segmentation period.

[0090] The principle of PSD output is to calculate the average centroid position of the laser spot on the PSD at each moment. It cannot distinguish whether it is a single moving spot or multiple spots existing simultaneously, thus producing dynamic errors. The reason for the dynamic errors is that the PSD's electronic circuitry is affected by the limited bandwidth, which makes the response of the electronic circuitry take time. If the laser spot moves at high speed on the PSD, that is, its speed exceeds the response time of the PSD's circuitry, the output signal cannot keep up with the actual displacement change, resulting in phase lag and amplitude attenuation. At the same time, if the jitter speed exceeds the bandwidth of the PSD's front-end circuitry, the output signal will be severely distorted and unable to reflect the true displacement of the spot. Specifically, in the measured outer diameter data sequence, this will cause a decrease in the amplitude of the outer diameter data sequence.

[0091] When the amplitude decreases, it leads to an amplitude difference between the outer diameter data sequence and the vibration data sequence at the same frequency, resulting in an excessively high frequency variation coefficient. Therefore, this invention further analyzes the separation between the frequency changes of the outer diameter data sequence and the changes of the vibration data sequence. Specifically, when the frequency of the vibration data sequence increases, the frequency of the outer diameter data sequence decreases compared to the vibration data sequence, indicating a higher probability of PSD separation.

[0092] For the m-th abnormal deviation period, obtain the period of the nearest non-abnormal deviation period before the m-th abnormal deviation period, and denot it as the previous normal segment before the m-th abnormal deviation period.

[0093] Spectrum diagrams of the outer diameter data sequence and vibration data sequence were obtained for the m-th abnormal deviation period and the previous normal period, respectively.

[0094] Based on the differences in vibration data and outer diameter data between the abnormal deviation period and the previous normal period, the abnormal deviation period is determined as the normal segmentation coefficient for the segmented period. Specifically:

[0095] Analyze the differences in vibration data between the abnormal deviation period and the previous normal period to determine the amplitude deviation coefficient. Specifically:

[0096] For any spectrum graph, the amplitude of all frequencies in the spectrum graph is normalized. The normalized amplitude value is used as the weight of the corresponding frequency. The frequency weighted sum of all frequencies in the spectrum graph is then obtained to obtain the frequency weighted mean of the spectrum graph. In the same spectrum graph, when normalizing the amplitude of all frequencies, the sum of the normalized amplitudes of all frequencies is limited to 1.

[0097] The frequency-weighted average of the vibration data spectrum during the abnormal deviation period is used as the numerator, and the frequency-weighted average of the outer diameter data during the abnormal deviation period is used as the denominator to obtain the common reference for the abnormal deviation period; the common reference for the previous normal period is determined; and the difference between the common references of the abnormal deviation period and the previous normal period is used as the amplitude deviation coefficient.

[0098] Analyze the differences in outer diameter data between the abnormal deviation period and the previous normal period to determine the outer diameter deviation coefficient. More specifically: obtain the maximum amplitude value among all frequencies in the spectrum of the outer diameter data corresponding to the abnormal deviation period, and use the frequency corresponding to the maximum amplitude value as the benchmark frequency; use the difference between the amplitude value of the maximum amplitude corresponding to the abnormal deviation period and the amplitude of the benchmark frequency in the spectrum of the outer diameter data corresponding to the previous normal period as the outer diameter deviation coefficient.

[0099] By combining the amplitude deviation coefficient and the outer diameter deviation coefficient, the abnormal deviation period is determined as the normal segmentation coefficient of the segmentation period; among them, the amplitude deviation coefficient and the outer diameter deviation coefficient are both positively correlated with the normal segmentation coefficient.

[0100] In this embodiment of the invention, taking the m-th abnormal deviation time period as an example, the normal segmentation coefficient of the m-th abnormal deviation time period is obtained. :

[0101] ;

[0102] in, The maximum amplitude of all frequencies in the spectrum of the outer diameter data during the m-th abnormal deviation period; In the outer diameter data of the previous normal period before the m-th abnormal deviation period, the maximum amplitude value is... The amplitude of the corresponding benchmark frequency; The outer diameter deviation coefficient is the value for the m-th abnormal deviation period. The frequency-weighted mean of the vibration data during the m-th abnormal deviation period is the frequency plot of the vibration data. The frequency-weighted mean of the outer diameter data for the m-th abnormal deviation period is the frequency-weighted average of the frequency plot. For the m-th abnormal deviation period, use the same reference. The frequency-weighted mean of the vibration data corresponding to the frequency plot of the previous normal period before the m-th abnormal deviation period; The frequency-weighted mean of the outer diameter data corresponding to the frequency plot of the previous normal period before the m-th abnormal deviation period; This is the reference for the previous normal period before the m-th abnormal deviation period; is the amplitude variation coefficient for the m-th abnormal deviation period; sigmoid is the Sigmoid function.

[0103] in, This indicates the attenuation of the amplitude. The greater the amplitude attenuation, the higher the probability of dynamic error in PSD measurement. The ratio of the frequency of the outer diameter data to the frequency of the vibration data is given. When dynamic error occurs, the frequency-weighted mean of the outer diameter data decreases, while the frequency-weighted mean of the vibration data increases relatively. In other words, the frequency difference between the two becomes separated, deviating from the covariant property.

[0104] Step S400: Analyze the percentage of time during which the inner and outer diameter data show abnormal changes during the abnormal deviation period, and determine the control abnormality coefficient for the abnormal deviation period.

[0105] The local concavity of a seamless steel pipe causes bulges on both sides, which is based on the law of constant volume and plastic flow characteristics of metallic materials.

[0106] When a seamless steel pipe is subjected to a concentrated external force, such as abnormal pressure from rollers, collisions during handling, or clamping, this force acts on the surface of the pipe. The metal in a localized area of ​​the seamless steel pipe surface will experience strong compressive stress. Under the action of compressive stress, metals with lower yield strength will undergo plastic deformation. Since the steel pipe is a continuous and constrained whole, the metal in the recessed area cannot simply disappear. This material must go to other places. The main flow paths of the material include along the axial direction, along the radial direction, and along the circumferential direction of the steel pipe. The combined action of the axial and radial directions will cause localized recesses, while the circumferential flow direction is subject to the shear force of the continuous steel pipe and the annular support force, which will cause the material flowing in the circumferential direction to bulge to a certain extent. As a result, the measured outer diameter data of the steel pipe will change under the overall trend of the outer diameter data corresponding to the abnormal deviation period.

[0107] Therefore, further analysis is conducted on the proportion of time during which the inner and outer diameter data show abnormal changes during the abnormal deviation period to determine the control anomaly coefficient for the abnormal deviation period. Specifically, for the outer diameter data corresponding to the m-th abnormal deviation period, the second derivative is calculated at each moment, that is, the second derivative of the inner and outer diameter data at different moments during the abnormal deviation period is determined; the moment when the second derivative is greater than 0 is taken as the moment when the outer diameter data shows abnormal changes; then, the cumulative duration of the moment when the outer diameter data shows abnormal changes is calculated, and its proportion in the abnormal deviation period is used as the control anomaly coefficient for the abnormal deviation period. ;in, The control anomaly coefficient for the m-th abnormal deviation period; This represents the number of moments in the m-th abnormal deviation period where the outer diameter data shows abnormal changes. This represents the length of the m-th abnormal deviation period, which is also the number of moments within the m-th abnormal deviation period.

[0108] When the second derivative is greater than 0, the characterization curve is concave, meaning that the two sides protrude from the middle. The larger the value, the larger the range of the suspected deviation radius segment occupied by this concavity, which means that the anomaly of the steel pipe is higher.

[0109] Step S500: Combine the normal segmentation coefficient and the control anomaly coefficient to determine the abnormal data value during the abnormal deviation period; when the abnormal data value exceeds the normal range, remeasure the outer diameter data under the corresponding abnormal deviation period.

[0110] The larger the control anomaly coefficient of the m-th abnormal deviation period, the more likely the m-th abnormal deviation period is caused by extrusion deformation. The smaller the normal segmentation coefficient of the m-th abnormal deviation period, the smaller the error measured by the oblique laser triangulation method, and the higher the possibility of anomalies in the steel pipe.

[0111] Therefore, the abnormal data values ​​for the m-th abnormal deviation period are determined by using the normal segmentation coefficient and the control abnormality coefficient. Specifically, the normal segmentation coefficient is negatively correlated to obtain the abnormal segmentation coefficient; the abnormal data values ​​for the abnormal deviation period are determined by combining the abnormal segmentation coefficient and the control abnormality coefficient. Both the abnormal segmentation coefficient and the control abnormality coefficient are positively correlated with the abnormal data values.

[0112] In some embodiments, the control anomaly coefficient is used as the numerator, the normal segmentation coefficient is used as the denominator, and the normalized ratio is used as the data anomaly value during the abnormal deviation period.

[0113] In other embodiments, the product of the anomaly segmentation coefficient and the control anomaly coefficient can also be used as the data anomaly value during the anomaly deviation period.

[0114] A preset anomaly detection threshold of 0.7 is set. When the value of an outlier exceeds this threshold, it indicates a higher probability of anomalies in that radius segment, suggesting the presence of significant vibration parameter interference in the data. Therefore, the data for that period of abnormal deviation is remeasured. It should be noted that the preset anomaly detection threshold can be adjusted by the implementer based on actual circumstances. The preset anomaly detection threshold of 0.7 in this invention was determined through long-term observation and analysis of historical data.

[0115] The remeasurement method is as follows: the seamless steel pipe is fixed in place by rollers and clamping equipment, and the midpoint of the m-th abnormal deviation period is oriented directly upward; the measuring module rotates around the steel pipe through a rotating mechanical structure to remeasure the outer diameter data of the m-th abnormal deviation period. The remeasured steel pipe radius sequence is the outer diameter of the steel pipe with outer diameter deviation after eliminating vibration interference.

[0116] Please see Figure 2 , Figure 2 This invention provides a schematic diagram of a precision seamless steel pipe outer diameter deviation measuring device, the device comprising:

[0117] The initial measurement module is used to acquire vibration data and outer diameter data of the steel pipe at each measurement point;

[0118] The initial time period determination module is used to analyze the vibration deviation between vibration data and outer diameter data to obtain the time period of abnormal deviation;

[0119] The first analysis module is used to determine the normal segmentation coefficient of the abnormal deviation period as the segmentation period based on the difference between the vibration data corresponding to the previous normal period and the difference between the outer diameter data corresponding to the abnormal deviation period and the previous normal period.

[0120] The second analysis module is used to analyze the percentage of time during which the inner and outer diameter data show abnormal changes during the abnormal deviation period, and to determine the control abnormality coefficient for the abnormal deviation period.

[0121] The data remeasurement module is used to determine the abnormal data values ​​during abnormal deviation periods by combining the normal segmentation coefficient and the control anomaly coefficient; when the abnormal data values ​​exceed the normal range, the outer diameter data under the corresponding abnormal deviation period is remeasured.

[0122] Alternatively, the transmission medium may be a wired link, such as, but not limited to, coaxial cable, fiber optic cable and digital subscriber line, or a wireless link, such as, but not limited to, wireless Fidelity (WIFI), Bluetooth and mobile device networks.

[0123] It should be noted that the device provided in the above embodiments is only an example of the division of the above functional modules. In actual applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the computer device can be divided into different functional modules to complete all or part of the functions described above.

[0124] This invention provides a schematic diagram of the structure of a computer device. Exemplarily, the computer device includes: a memory, a processor, and a computer program stored in the memory and running on the processor, wherein when the processor executes the computer program, the computer device can perform the aforementioned method for measuring the outer diameter deviation of any precision seamless steel pipe.

[0125] Furthermore, embodiments of the present invention also protect an apparatus that may include a memory and a processor, wherein the memory stores executable program code, and the processor is used to call and execute the executable program code to perform the precision seamless steel pipe outer diameter deviation measurement method provided in the embodiments of the present invention.

[0126] In this embodiment of the invention, the device can be divided into functional modules according to the above method example. For example, each module can correspond to a separate function, or two or more functions can be integrated into one processing module. The integrated module can be implemented in hardware. It should be noted that the module division in this embodiment is illustrative and is only a logical functional division. In actual implementation, there may be other division methods.

[0127] When each module is divided according to its function, the device may also include a signal uploading module, a determination module, and an adjustment module. It should be noted that all relevant content regarding the steps involved in the above method embodiments can be referenced from the functional descriptions of the corresponding modules, and will not be repeated here.

[0128] It should be understood that the apparatus provided in this embodiment of the invention is used to perform the above-described method for measuring the outer diameter deviation of precision seamless steel pipes, and thus can achieve the same effect as the above-described implementation method.

[0129] When using integrated units, the device may include a processing module and a storage module. When applied to a device, the processing module can be used to control and manage the device's operations. The storage module can be used to support the device in executing program code, etc. The processing module may be a processor or a controller, which can implement or execute various exemplary logic blocks, modules, and circuits as described in this disclosure. The processor may also be a combination that implements computing functions, such as a combination of one or more microprocessors, a combination of Digital Signal Processing (DSP) and a microprocessor, etc., and the storage module may be a memory.

[0130] In addition, the device provided in the embodiments of the present invention may specifically be a chip, component or module. The chip may include a connected processor and a memory. The memory is used to store instructions. When the processor calls and executes the instructions, the chip can execute the precision seamless steel pipe outer diameter deviation measurement method provided in the above embodiments.

[0131] This invention also provides a computer-readable storage medium storing computer program code. When the computer program code is run on a computer, the computer executes the aforementioned method steps to implement the precision seamless steel pipe outer diameter deviation measurement method provided in the above embodiments.

[0132] This invention also provides a computer program product that, when run on a computer, causes the computer to perform the aforementioned steps to implement the method for measuring the outer diameter deviation of precision seamless steel pipes provided in the above embodiments.

[0133] In this invention, the apparatus, computer-readable storage medium, computer program product, or chip provided in the embodiments are all used to execute the corresponding methods described above. Therefore, the beneficial effects they achieve can be referred to the beneficial effects in the corresponding methods described above, and will not be repeated here. Through the above description of the embodiments, those skilled in the art will understand that, for the sake of convenience and brevity, only the division of the above functional modules is used as an example. In practical applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above. In the embodiments provided by this invention, it should be understood that the disclosed apparatus and method can be implemented in other ways.

[0134] The device embodiments described above are merely illustrative. For example, the division of modules or units is only a logical functional division. In actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another device, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between devices or units may be electrical, mechanical, or other forms.

[0135] It should also be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or terminal device that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or terminal device. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or terminal device that includes said element.

[0136] It should be noted that the order of the above embodiments of the present invention is merely for descriptive purposes and does not represent the superiority or inferiority of the embodiments. The processes depicted in the accompanying drawings do not necessarily require a specific or sequential order to achieve the desired result. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0137] The various embodiments in this specification are described in a progressive manner. The same or similar parts between the various embodiments can be referred to each other. Each embodiment focuses on describing the differences from other embodiments.

[0138] The above content is only a specific embodiment of the present invention, but the protection scope of the present invention is not limited thereto. Any changes or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in the present invention should be included within the protection scope of the present invention.

Claims

1. A method of measuring the outside diameter deviation of a precision seamless steel pipe, characterized by, The method comprises the following steps: Obtaining vibration data and outer diameter data of the precision seamless steel pipe at each measurement point; Analyzing the vibration deviation between the vibration data and the outer diameter data to obtain an abnormal deviation period; According to the difference of the vibration data corresponding to the abnormal deviation period and the previous normal period, the difference of the outer diameter data corresponding to the abnormal deviation period and the previous normal period, determining the normal segmentation coefficient of the abnormal deviation period as a segmentation period; Analyzing the proportion of the time length of the abnormal change of the outer diameter data in the abnormal deviation period to determine the control abnormal coefficient of the abnormal deviation period; Combining the normal segmentation coefficient and the control abnormal coefficient to determine the data abnormal value of the abnormal deviation period; when the data abnormal value exceeds the normal range, re-measuring the outer diameter data under the corresponding abnormal deviation period; The method for obtaining the data abnormal value is: performing negative correlation mapping on the normal segmentation coefficient to obtain an abnormal segmentation coefficient; and taking the product value of the abnormal segmentation coefficient and the control abnormal coefficient as the data abnormal value of the abnormal deviation period.

2. The method of measuring the outside diameter deviation of a precision seamless steel pipe according to claim 1, characterized by The method for analyzing the vibration deviation between the vibration data and the outer diameter data to obtain the abnormal deviation period comprises: Analyzing the deviation between the frequency spectrum graphs of the vibration data and the outer diameter data at the same time to determine a frequency variation coefficient; The abnormal deviation period is composed of the continuous time period corresponding to the frequency variation coefficient greater than the preset variation threshold.

3. The method of measuring the outside diameter deviation of a precision seamless steel pipe according to claim 2, characterized by The method for analyzing the deviation between the frequency spectrum graphs of the vibration data and the outer diameter data at the same time to determine the frequency variation coefficient comprises: Taking any time as a target time and any frequency as a target frequency; Calculating the difference between the amplitude of the target frequency in the frequency spectrum graph corresponding to the vibration data and the frequency spectrum graph corresponding to the outer diameter data at the target time as the amplitude measurement difference of the target frequency; Determining the contribution weight corresponding to the frequency based on the size of the frequency; For the target frequency, combining the amplitude measurement difference and the contribution weight to obtain a single variation coefficient of the target frequency; Comprehensively determining the frequency variation coefficient at the target time by comprehensively determining the single variation coefficients of all frequencies at the target time.

4. The method of measuring the outside diameter deviation of a precision seamless steel pipe according to claim 1, characterized by The method for determining the normal segmentation coefficient of the abnormal deviation period as a segmentation period according to the difference of the vibration data corresponding to the abnormal deviation period and the previous normal period, the difference of the outer diameter data corresponding to the abnormal deviation period and the previous normal period comprises: Analyzing the difference of the vibration data corresponding to the abnormal deviation period and the previous normal period to determine an amplitude deviation coefficient; Analyzing the difference of the outer diameter data corresponding to the abnormal deviation period and the previous normal period to determine an outer diameter deviation coefficient; Combining the amplitude deviation coefficient and the outer diameter deviation coefficient to determine the normal segmentation coefficient of the abnormal deviation period as a segmentation period; wherein the amplitude deviation coefficient and the outer diameter deviation coefficient are in a positive correlation relationship with the normal segmentation coefficient.

5. The method of measuring the outside diameter deviation of a precision seamless steel pipe according to claim 4, characterized by The method for analyzing the difference of the outer diameter data corresponding to the abnormal deviation period and the previous normal period to determine the outer diameter deviation coefficient comprises: Obtaining the amplitude maximum value in all frequencies in the frequency spectrum graph of the outer diameter data corresponding to the abnormal deviation period, and taking the frequency corresponding to the amplitude maximum value as a reference frequency; The difference between the amplitude maximum value corresponding to the abnormal deviation period and the amplitude of the reference frequency in the frequency spectrum of the outer diameter data corresponding to the previous normal period is taken as an outer diameter deviation coefficient.

6. The method of measuring the outside diameter deviation of a precision seamless steel pipe according to claim 4, wherein The difference between the vibration data corresponding to the abnormal deviation period and the previous normal period is analyzed to determine an amplitude deviation coefficient, including: For any frequency spectrum, the amplitudes of all frequencies in the frequency spectrum are normalized, and the normalized result value of the amplitude is taken as the weight of the corresponding frequency. The weighted sum of all frequencies in the frequency spectrum is obtained to obtain the frequency weighted mean value corresponding to the frequency spectrum; The frequency weighted mean value of the frequency spectrum of the vibration data in the abnormal deviation period is taken as the numerator, and the frequency weighted mean value of the outer diameter data in the abnormal deviation period is taken as the denominator to obtain the homologous reference of the abnormal deviation period; The homologous reference of the previous normal period is determined; The difference between the homologous references of the abnormal deviation period and the previous normal period is taken as the amplitude deviation coefficient.

7. The method of measuring the outside diameter deviation of a precision seamless steel pipe according to claim 1, wherein The length proportion of the abnormal change of the outer diameter data in the abnormal deviation period is analyzed to determine the control abnormal coefficient of the abnormal deviation period, including: The second derivative of the outer diameter data at different times in the abnormal deviation period is determined; The time when the second derivative is greater than 0 is determined as the time when the outer diameter data abnormally changes; The proportion of the cumulative length of the time when the outer diameter data abnormally changes is taken as the control abnormal coefficient of the abnormal deviation period.

8. A device for measuring the outer diameter deviation of a precision seamless steel pipe, characterized in that, The device includes the following modules: An initial measurement module for obtaining vibration data and outer diameter data of the steel pipe at each measurement point; A period initial determination module for analyzing the vibration deviation between the vibration data and the outer diameter data to obtain an abnormal deviation period; A first analysis module for determining a normal segmentation coefficient of the abnormal deviation period as a segmentation period according to the difference between the vibration data corresponding to the abnormal deviation period and the previous normal period, and the difference between the outer diameter data corresponding to the abnormal deviation period and the previous normal period; A second analysis module for analyzing the length proportion of the abnormal change of the outer diameter data in the abnormal deviation period to determine the control abnormal coefficient of the abnormal deviation period; A data re-measurement module for determining a data abnormal value of the abnormal deviation period in combination with the normal segmentation coefficient and the control abnormal coefficient; when the data abnormal value exceeds the normal range, the outer diameter data under the corresponding abnormal deviation period is re-measured; The data abnormal value is obtained by: negatively correlating the normal segmentation coefficient to obtain an abnormal segmentation coefficient; and taking the product value of the abnormal segmentation coefficient and the control abnormal coefficient as the data abnormal value of the abnormal deviation period.

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