Data processing method, device and equipment for pipeline magnetic flux leakage internal detection and storage medium

Abstract

The application discloses a pipeline magnetic flux leakage internal detection data processing method, device and equipment and a computer readable storage medium. The method comprises the following steps: acquiring a magnetic flux leakage data block and a sampling starting time corresponding to each magnetic flux leakage data block through a magnetic flux leakage detector; wherein a same sampling channel in the magnetic flux leakage detector continuously collects a preset number of magnetic flux leakage data to form a magnetic flux leakage data block; determining a sampling time corresponding to each magnetic flux leakage data according to the sampling starting time corresponding to each magnetic flux leakage data block; preliminarily aligning the magnetic flux leakage data between different sampling channels based on the sampling time; forming a corresponding magnetic flux leakage waveform from the preliminarily aligned magnetic flux leakage data, and performing feature alignment according to the waveform features of the magnetic flux leakage waveform. The application provides the possibility of further improving the sampling frequency of each sampling channel of the magnetic flux leakage detector and aligning and adjusting the magnetic flux leakage data of each sampling channel, thereby ensuring the accuracy of magnetic flux leakage analysis.

Description

Technical Field

[0001] This invention relates to the field of pipeline flaw detection technology, and in particular to a data processing method, apparatus, equipment, and computer-readable storage medium for pipeline magnetic flux leakage detection. Background Technology

[0002] Pipeline magnetic flux leakage (MFL) testing is mainly used to detect cracks and damage on metal pipelines used for transporting gasoline and oil. Generally, the MFL detector is placed inside the pipeline and moves sequentially through different locations of the pipeline as the fluid flows through it, collecting MFL information at different locations.

[0003] Currently, conventional magnetic flux leakage detectors contain multiple probes for detecting magnetic flux leakage in pipelines from different directions. Each probe contains multiple sampling channels, and each sampling channel collects a set of magnetic flux leakage data. By analyzing the different magnetic flux leakage data from various probes, the extent of pipeline damage can be determined, allowing for timely maintenance and repair of the pipeline.

[0004] Each sampling channel in each probe acquires data at a fixed sampling frequency. In practical applications, a higher sampling frequency results in clearer and more accurate magnetic flux leakage data that reflects the pipeline's magnetic flux leakage information, thus facilitating more accurate analysis of pipeline damage. However, the sampling frequency of existing magnetic flux leakage detectors is currently insufficient to meet the requirements for high-resolution sampling. Summary of the Invention

[0005] The purpose of this invention is to provide a data processing method, apparatus, device, and computer-readable storage medium for pipeline magnetic flux leakage detection, which can improve the accuracy of pipeline damage detection to a certain extent.

[0006] To solve the above-mentioned technical problems, the present invention provides a data processing method for pipeline magnetic flux leakage detection, comprising:

[0007] A magnetic flux leakage data block and the sampling start time corresponding to each magnetic flux leakage data block are obtained by a magnetic flux leakage detector; wherein, a magnetic flux leakage data block is formed by continuously collecting a preset number of magnetic flux leakage data in the same sampling channel of the magnetic flux leakage detector; the sampling start time is the sampling time corresponding to the first magnetic flux leakage data in the magnetic flux leakage data block.

[0008] Based on the sampling start time corresponding to each of the magnetic flux leakage data blocks, the sampling time corresponding to each of the magnetic flux leakage data blocks is determined;

[0009] Based on the sampling time, the leakage magnetic data between the different sampling channels are initially aligned;

[0010] The initially aligned magnetic leakage data is used to form a corresponding magnetic leakage waveform, and feature alignment is performed based on the waveform characteristics of the magnetic leakage waveform.

[0011] Optionally, preliminary alignment of the leakage magnetic data between different sampling channels is performed based on the sampling time, including:

[0012] Select a reference sampling channel from all sampling channels;

[0013] Each leakage magnetic field data in the reference sampling channel is assigned a sequence number according to its corresponding sampling time;

[0014] The leakage magnetic field data of each sampling channel is set with a sequence number that is aligned with the sequence number of each leakage magnetic field data in the reference sampling channel, so that the sequence number of the leakage magnetic field data in each sampling channel is the same as the sequence number of the leakage magnetic field data with the closest sampling time in the reference sampling channel.

[0015] Optionally, feature alignment is performed based on the waveform characteristics of the leakage flux waveform, including:

[0016] The leakage magnetic waveform is visualized.

[0017] Receive a calibration command to calibrate the timing segment where a specific waveform is located in the visualized leakage magnetic waveform;

[0018] Extreme point identification is performed based on the specific waveform corresponding to the time segment contained in the calibration instruction to obtain the extreme point sequence number of the specific waveform corresponding to each sampling channel;

[0019] Each sampling channel is offset according to the offset between the extreme point sequence number of each sampling channel and the extreme point sequence number of the reference sampling channel, so that the extreme point sequence number of each sampling channel is the same as the extreme point sequence number of the reference sampling channel.

[0020] Optionally, after aligning the extreme point sequence numbers of each of the sampling channels, the method further includes:

[0021] Based on the location of the timing segment and the corresponding offset of the leakage magnetic waveform of each sampling channel, the misalignment period and misalignment offset of the leakage magnetic waveform between each sampling channel are determined.

[0022] Based on the misalignment period and the misalignment offset, the leakage magnetic waveform of each sampling channel is adjusted once every corresponding misalignment period.

[0023] Optionally, each sampling channel is offset according to the offset between the extreme point sequence number of each sampling channel and the extreme point sequence number of the reference sampling channel, including:

[0024] Each of the sampling channels is offset according to its corresponding offset;

[0025] Determine the maximum gap interval and the maximum overlap interval caused by offset in each of the sampling channels;

[0026] The magnetic flux leakage data corresponding to the positions of the maximum gap interval and the maximum overlap interval in each of the sampling channels, including the reference sampling channel, are cut and deleted.

[0027] A data processing device for pipeline magnetic flux leakage detection includes:

[0028] A data block acquisition module is used to acquire magnetic flux leakage data blocks and the sampling start time corresponding to each magnetic flux leakage data block through a magnetic flux leakage detector; wherein, a magnetic flux leakage data block is formed by continuously acquiring a preset number of magnetic flux leakage data in the same sampling channel of the magnetic flux leakage detector; and the sampling start time is the sampling time corresponding to the first magnetic flux leakage data in the magnetic flux leakage data block.

[0029] The timestamp acquisition module is used to determine the sampling time corresponding to each magnetic leakage data in each magnetic leakage data block based on the sampling start time corresponding to each magnetic leakage data block;

[0030] A preliminary alignment module is used to perform preliminary alignment of the magnetic flux leakage data between different sampling channels based on the sampling time.

[0031] The waveform alignment module is used to form a corresponding leakage magnetic waveform from the initially aligned leakage magnetic data, and to perform feature alignment based on the waveform characteristics of the leakage magnetic waveform.

[0032] Optionally, the preliminary alignment module is specifically used to select a reference sampling channel among all sampling channels; set a sequence number for each leakage magnetic data in the reference sampling channel according to the corresponding sampling time; and set a sequence number for the leakage magnetic data in each sampling channel that is aligned with the sequence number of each leakage magnetic data in the reference sampling channel, so that the sequence number of the leakage magnetic data in each sampling channel is the same as the sequence number of the leakage magnetic data with the closest sampling time in the reference sampling channel.

[0033] Optionally, the waveform alignment module is used to visualize the leakage magnetic waveform; receive a calibration instruction to calibrate the timing segment where a specific waveform in the visualized leakage magnetic waveform is located; identify extreme points according to the specific waveform corresponding to the timing segment included in the calibration instruction, and obtain the extreme point sequence number of the specific waveform corresponding to each sampling channel; offset each sampling channel according to the offset between the extreme point sequence number of each sampling channel and the extreme point sequence number of the reference sampling channel, so that the extreme point sequence number of each sampling channel is the same as the extreme point sequence number of the reference sampling channel.

[0034] A data processing device for pipeline magnetic flux leakage detection includes a magnetic flux leakage detector and a host computer communicatively connected to the magnetic flux leakage detector; the magnetic flux leakage detector includes multiple probes, each probe including a microprocessor, a memory and multiple sampling channels;

[0035] The microprocessor is used to store a preset number of leakage magnetic data collected by each sampling channel as a leakage magnetic data block and the sampling start time of the first leakage magnetic data in each leakage magnetic data block in the memory;

[0036] The host computer is used to obtain the magnetic flux leakage data blocks of different probes and different sampling channels and the corresponding sampling timestamps through communication connections with each of the microprocessors, and to execute the steps of the data processing method for pipeline magnetic flux leakage detection as described in any of the above claims.

[0037] A computer-readable storage medium storing a computer program that is executed by a processor to implement the steps of the data processing method for internal detection of magnetic flux leakage in pipelines as described in any of the preceding claims.

[0038] The present invention provides a data processing method, apparatus, device, and computer-readable storage medium for pipeline magnetic flux leakage detection. The method may include: acquiring magnetic flux leakage data blocks through a magnetic flux leakage detector and a sampling start time corresponding to each magnetic flux leakage data block; wherein, a magnetic flux leakage data block is formed by continuously acquiring a preset number of magnetic flux leakage data in the same sampling channel of the magnetic flux leakage detector; the sampling start time is the sampling time corresponding to the first magnetic flux leakage data in the magnetic flux leakage data block; determining the sampling time corresponding to each magnetic flux leakage data in each magnetic flux leakage data block according to the sampling start time corresponding to each magnetic flux leakage data block; performing preliminary alignment of the magnetic flux leakage data between different sampling channels based on the sampling time; forming a corresponding magnetic flux leakage waveform from the preliminary aligned magnetic flux leakage data, and performing feature alignment according to the waveform characteristics of the magnetic flux leakage waveform.

[0039] In this application, the magnetic flux leakage data obtained by the magnetic flux leakage detector is uploaded in the form of magnetic flux leakage data blocks. Only the first magnetic flux leakage data in each block has a sampling start time. By combining the number of magnetic flux leakage data in each block, the sampling time of each magnetic flux leakage data can be determined. This means that when each sampling channel of the magnetic flux leakage detector collects magnetic flux leakage data, it is not necessary to read and record a corresponding sampling time for each magnetic flux leakage data through the clock module. This greatly reduces the frequency and time spent by the magnetic flux leakage detector reading the clock module, providing the possibility to further increase the sampling frequency of each sampling channel of the magnetic flux leakage detector. Furthermore, the magnetic flux leakage data of each sampling channel is aligned and adjusted based on the sampling time of each magnetic flux leakage data, which helps to ensure the accuracy of subsequent magnetic flux leakage analysis based on the magnetic flux leakage data. Attached Figure Description

[0040] To more clearly illustrate the technical solutions of 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.

[0041] Figure 1 This is a flowchart illustrating a data processing method for internal detection of magnetic flux leakage in pipelines according to this application;

[0042] Figure 2 A schematic diagram of a magnetic flux leakage waveform provided in an embodiment of this application;

[0043] Figure 3 for Figure 2 A schematic diagram of the leakage magnetic field waveform after waveform feature alignment;

[0044] Figure 4 A partially enlarged schematic diagram of a leakage magnetic field waveform provided in an embodiment of this application;

[0045] Figure 5 This is a structural block diagram of a data processing device for internal detection of magnetic flux leakage in pipelines provided in an embodiment of the present invention. Detailed Implementation

[0046] Currently, conventional magnetic flux leakage detectors typically contain multiple probes, each with multiple sampling channels (i.e., magnetic flux leakage sensors). In addition, the detector also includes a processor, memory, and other components. When each sampling channel of each probe acquires magnetic flux leakage data, the processor needs to read the time data from the clock module to obtain the corresponding sampling time. This magnetic flux leakage data and its corresponding sampling time are then stored in the memory for uploading to the host computer. Obviously, the higher the frequency of magnetic flux leakage data acquisition by each sampling channel, the more frequently the processor needs to read the clock module, and the more frequently it needs to store the magnetic flux leakage data and sampling time. However, reading the clock module and storing data both require processing time, which limits the sampling frequency of magnetic flux leakage data acquisition by the sampling channels, thus affecting the accuracy of pipeline damage analysis based on magnetic flux leakage data to some extent.

[0047] Therefore, this application provides a technical solution that is beneficial to increasing the sampling frequency of magnetic flux leakage data and improving the accuracy of pipeline damage detection results.

[0048] To enable those skilled in the art to better understand the present invention, the invention will be further described in detail below with reference to the accompanying drawings and specific embodiments. Obviously, the described embodiments are merely some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0049] like Figure 1 As shown, Figure 1 This is a flowchart illustrating a data processing method for internal detection of magnetic flux leakage in pipelines according to this application. The data processing method may include:

[0050] S11: The magnetic flux leakage data block obtained by the magnetic flux leakage detector and the sampling start time corresponding to each magnetic flux leakage data block.

[0051] In the magnetic flux leakage detector, a magnetic flux leakage data block is formed by continuously collecting a preset number of magnetic flux leakage data in the same sampling channel; the sampling start time is the sampling time corresponding to the first magnetic flux leakage data in the magnetic flux leakage data block.

[0052] In other words, in this embodiment, when the magnetic flux leakage detector collects magnetic flux leakage data, it does not read the time information of the clock module and store the magnetic flux leakage data and time once for each magnetic flux leakage data collected. Instead, after collecting a preset amount of magnetic flux leakage data in the same sampling channel, the preset amount of magnetic flux leakage data is stored as a magnetic flux leakage data block. Furthermore, the processor only reads the time information of the clock module once when the first magnetic flux leakage data in each magnetic flux leakage data block is collected and stored, and the sampling time of the first magnetic flux leakage data is used as the sampling start time of the entire magnetic flux leakage data block.

[0053] Taking a preset quantity of 1000 magnetic flux leakage data blocks as an example, it is clear that in this embodiment, for every 1000 magnetic flux leakage data collected in each sampling channel, the processor in the magnetic flux leakage detector only needs to read the clock module once, which greatly reduces the time spent reading the time data of the clock module. At the same time, the storage frequency of the magnetic flux leakage data in the memory is also greatly reduced, which can also reduce the amount of computation of the processor to a certain extent, thereby providing support for improving the sampling frequency of the sampling channel of the magnetic flux leakage detector.

[0054] It should be noted that conventional magnetic flux leakage detectors typically contain multiple probes, each with multiple sampling channels. All probes are centrally managed by a processor, which stores and uploads the magnetic flux leakage data for each sampling channel of each probe.

[0055] However, this embodiment further considers that all magnetic flux leakage data collected by each probe and each sampling channel is centrally managed by the same processor, which will also put a lot of computational pressure on the processor. Furthermore, if the processor fails to store data due to a malfunction, the entire magnetic flux leakage detector will be unable to complete the magnetic flux leakage detection.

[0056] Therefore, in this embodiment, the magnetic flux leakage detector can be configured with an independent microprocessor and memory in each probe. Each microprocessor only processes and stores the magnetic flux leakage data collected by each sampling channel of its probe, thereby reducing the computational pressure of each microprocessor to a certain extent. On this basis, each microprocessor works independently. Even if one microprocessor fails, the host computer can still obtain the magnetic flux leakage data collected by other probes based on other microprocessors, thereby completing the magnetic flux leakage detection of the pipeline.

[0057] It is understood that the key to this embodiment is that the magnetic flux leakage data in the magnetic flux leakage detector is stored in the form of data blocks, and only the sampling time of the first magnetic flux leakage data in the data block is read, thereby reducing the computational pressure on the processor and supporting the improvement of the sampling frequency of the sampling channels. The magnetic flux leakage detector can have only one processor, which centrally manages and stores the magnetic flux leakage data collected from each sampling channel; alternatively, each probe can have an independently configured microprocessor, with each microprocessor independently managing and storing the magnetic flux leakage data collected from each sampling channel of its respective probe. This application does not impose specific limitations on this approach.

[0058] S12: Determine the sampling time corresponding to each leakage magnetic data in each leakage magnetic data block based on the sampling start time corresponding to each leakage magnetic data block.

[0059] It should be noted that, since each preset number of leakage magnetic data is collected by the same sampling channel, the preset number of leakage magnetic data is formed into a leakage magnetic data block for storage, the difference between the sampling start times of two adjacent leakage magnetic data blocks collected by the same sampling channel can be regarded as the sampling period for collecting all leakage magnetic data in a leakage magnetic data block.

[0060] Obviously, the sampling time interval between two adjacent collections of leakage magnetic data in the same sampling channel can be obtained based on the ratio of the sampling period to the preset number. Accordingly, based on the sampling start time and sampling time interval corresponding to each leakage magnetic data block, the sampling time corresponding to each sampled data in each leakage magnetic data block can be determined sequentially.

[0061] In addition, the sampling frequency of each sampling channel is usually preset. It is also possible to determine the sampling time interval between adjacent leakage magnetic data in the same sampling channel based on the preset sampling frequency, and then combine this with the sampling start time to determine the sampling time corresponding to each leakage magnetic data. This application does not impose specific restrictions on this.

[0062] Additionally, it should be noted that when reading time information in the clock module, the time information data is generally read in long format, i.e., dd hh:MM:ss,ffff (day: hour: minute: second: millisecond). However, considering that this time information data format is not convenient for subsequent calculations and occupies a large amount of memory, the sampling start time and sampling time in this embodiment can be converted into a timestamp format in milliseconds, as shown in Table 1 below. Table 1 is a table for converting long data into timestamps.

[0063] Table 1:

[0064] Format Long type Timestamp (ms) time 2021-09-2811:12:05 1632798725000

[0065] The timestamp 1632798725000ms in Table 1 is the total number of milliseconds that have elapsed from 00:00:00 on January 1, 1970 (UTC, Coordinated Universal Time) to 11:12:05 on September 28, 2021.

[0066] In practical applications, subsequent calculations are convenient. A standard timestamp starting point closer to the current time can be reset, and the timestamps corresponding to each sampling start time and sampling time can be subtracted from the timestamps between the standard timestamps to represent the final sampling start timestamp and sampling timestamp.

[0067] For example, for a sampling start time of 2021-09-28 11:12:05, the timestamp corresponding to 2021-01-01 00:00:00 can be used as the standard timestamp, and the difference between 1632798725000ms and the standard timestamp can be used as the sampling start timestamp. This facilitates subsequent calculations and reduces the amount of time data stored. When determining the sampling time for each leakage magnetic field data point, the sampling time can be calculated directly using the sampling start timestamp, and the final sampling time will also be represented as a timestamp.

[0068] S13: Perform preliminary alignment of leakage magnetic data between different sampling channels based on sampling time.

[0069] S14: The initially aligned time-aligned magnetic flux leakage data is used to form the corresponding magnetic flux leakage waveform, and feature alignment is performed based on the waveform characteristics of the magnetic flux leakage waveform.

[0070] As mentioned earlier, a magnetic flux leakage detector typically consists of multiple probes, each containing multiple sampling channels. Theoretically, after the magnetic flux leakage detector starts detecting, the start time and sampling period of each sampling channel are the same. However, in actual detection, there will be some time deviation, causing the sampling time recorded for the magnetic flux leakage data acquired at the same time by each sampling channel to be different, resulting in a shift in the sampling time of the magnetic flux leakage data acquired by each sampling channel.

[0071] It is often difficult to determine the offset in sampling time for different sampling channels based solely on magnetic flux leakage data. However, it is certain that when the magnetic flux leakage detector passes through certain specific locations on the pipeline, such as the circumferential weld, the magnetic flux leakage data collected by each sampling channel will simultaneously appear on the corresponding waveform. Theoretically, the sampling time corresponding to the magnetic flux leakage data that forms a specific waveform collected by each sampling channel at locations with special structural characteristics on the pipeline should be the same. Therefore, this can be used as a basis to adjust the sampling time of the magnetic flux leakage data with a specific waveform as a reference.

[0072] The sampling data of each sampling channel can be time-aligned according to the sampling time. Then, the leakage magnetic data corresponding to each sampling channel after time alignment can be converted into leakage magnetic waveforms. The leakage magnetic data can be aligned based on specific waveform characteristics in the leakage magnetic waveform, thereby providing data basis for subsequent detection of pipeline damage based on leakage magnetic waveforms.

[0073] Optionally, the process of performing preliminary alignment of leakage magnetic data between different sampling channels based on sampling time may include:

[0074] S131: Select a reference sampling channel from all sampling channels.

[0075] S132: Set the sequence number for each leakage magnetic data in the reference sampling channel according to the corresponding sampling time.

[0076] S133: Set the sequence number of the leakage magnetic data in each sampling channel to be aligned with the sequence number of each leakage magnetic data in the reference sampling channel, so that the sequence number of the leakage magnetic data in each sampling channel is the same as the sequence number of the leakage magnetic data with the closest sampling time in the reference sampling channel.

[0077] In this embodiment, the sampling data corresponding to each sampling channel can be arranged according to the time axis. Since the starting sampling time points of each sampling channel may be different, the leakage magnetic field data obtained from the initial time period with the earlier sampling time in each sampling channel can be cut off, so that the starting sampling time point of each sampling channel is aligned with the sampling channel with the latest starting sampling time point.

[0078] It is understood that the leakage magnetic field data of each sampling channel are acquired at the same time interval, meaning that the leakage magnetic field data of each sampling channel is a set of leakage magnetic field data. Therefore, one of the sampling channels can be selected as the reference sampling channel, and the corresponding sequence number of each leakage magnetic field data point in that reference sampling channel can be assigned according to the sampling time sequence. Then, using the sequence number of each leakage magnetic field data point in the reference sampling channel as a reference, the sequence numbers of each leakage magnetic field data point in the other sampling channels can be assigned accordingly. When setting the sequence number of the leakage magnetic field data in each sampling channel, the sampling time of each leakage magnetic field data point in that sampling channel can be compared with the sampling time of the leakage magnetic field data in the reference sampling channel. This ensures that the sequence number of the leakage magnetic field data point in the sampling channel with the closest sampling time to the sampling time in the reference sampling channel is the same, thereby achieving sequence number alignment between the sampling channel and the reference sampling channel.

[0079] The reason for setting a sequence number for the leakage magnetic flux data of each sampling channel and aligning the sequence numbers of the leakage magnetic flux data of each sampling channel in this embodiment is to prepare for subsequent alignment adjustment based on waveform features. This makes the offset reflected in the form of the difference in sequence numbers when aligning waveform features later, which is simpler than the sampling time difference. In addition, when analyzing pipeline damage using leakage magnetic flux data later, the leakage magnetic flux data should also be analyzed in the form of time-series data.

[0080] When determining the sequence number of leakage magnetic data for other sampling channels based on the sequence number of the reference sampling channel, there may be a sequence number gap between adjacent leakage magnetic data for each sampling channel. That is to say, the sequence numbers of two adjacent leakage magnetic data can differ by 1 (normally they differ by 1) or by 2 (i.e., there is a sequence number gap), but there should be no duplicate sequence numbers.

[0081] Furthermore, there are no specific requirements in this application regarding the selection of the aforementioned reference sampling channels; any one of the sampling channels may be selected as the reference sampling channel.

[0082] After setting the corresponding sequence number and aligning the sequence numbers for the leakage magnetic data of each sampling channel, the further process of feature alignment of the leakage magnetic waveform corresponding to the leakage magnetic data may include:

[0083] S141: Visualize the leakage flux waveform.

[0084] S142: Receive a calibration command to calibrate the timing segment where a specific waveform in the visualized leakage magnetic waveform is located.

[0085] S143: Identify extreme points based on the specific waveforms corresponding to the timing segments included in the calibration instructions, and obtain the extreme point sequence number of the specific waveforms corresponding to each sampling channel.

[0086] S144: Offset each sampling channel according to the offset between the extreme point sequence number of each sampling channel and the extreme point sequence number of the reference sampling channel, so that the extreme point sequence number of each sampling channel is the same as the extreme point sequence number of the reference sampling channel.

[0087] Reference Figures 2 to 4 , Figure 2 A schematic diagram of a magnetic flux leakage waveform provided in an embodiment of this application; Figure 3 for Figure 2 A schematic diagram of the leakage magnetic field waveform after waveform feature alignment; Figure 4 This is a partially enlarged schematic diagram of a leakage magnetic waveform provided in an embodiment of this application.

[0088] contrast Figure 2 and Figure 3 , Figure 2 and Figure 3 The waveform exhibiting a significant amplitude fluctuation region corresponds to the magnetic flux leakage waveform measured at the location of the circumferential weld in the pipeline. Theoretically, the time for each sampling channel to measure the magnetic flux leakage waveform corresponding to the circumferential weld should be the same, i.e., as shown below. Figure 3 As shown, the leakage magnetic flux waveform corresponding to the circumferential weld of each sampling channel should be as follows: Figure 3 The image shows an aligned state. Therefore, it is necessary to... Figure 2 The waveform diagram shown is adjusted to form Figure 3 The alignment status is shown.

[0089] It should be noted that computers are currently unable to identify the waveform characteristics of specific waveforms within magnetic leakage waveforms. Figure 2 and Figure 3 The image shown is a filtered waveform with noise removed and only a very small portion extracted. In practical applications, the actual flux leakage waveform is much larger than that shown. Figure 2 and Figure 3 The waveform shown is complex; if a computer could directly recognize it... Figure 2 A specific waveform can be analyzed directly, so manual calibration is still required when aligning waveform features.

[0090] First, the leakage magnetic flux waveforms of each sampling channel are visualized using a display screen. Based on the leakage magnetic flux waveforms displayed on the screen, the user can manually perform a large first time-series calibration. This first time-series region contains the specific waveforms corresponding to the same circumferential weld in each sampling channel of the pipeline, such as... Figure 2 The large rectangle in the diagram represents the interval corresponding to the first time series interval.

[0091] Based on this, since the relative offset between the leakage magnetic waveforms of different sampling channels on the same probe is generally relatively small, while the larger offset is the waveform deviation between sampling channels of different probes, in actual waveform feature-based alignment, the leakage magnetic waveforms of different sampling channels on the same probe can be aligned first. Users can further delineate and mark the specific waveforms corresponding to each sampling channel on the same probe, such as... Figure 2 The small rectangle shown represents the interval corresponding to the second time series interval.

[0092] In practice, when adjusting waveform characteristics, after the user defines the second time interval by calibrating, the extreme points of the waveforms in the second time interval of each sampling channel within each small rectangle can be identified, and the offset can be determined based on the sequence number corresponding to the identified extreme points.

[0093] Reference Figure 4 , Figure 4Each of the four sampling channels shown contains a specific waveform, and the specific waveforms of the four sampling channels correspond to the waveforms of the same circumferential weld on the pipe. Figure 4 Taking sampling channel one as the reference sampling channel as an example, it is clear that for sampling channel one, the maximum value sequence number of its corresponding specific waveform is i+3, while the maximum value sequence number of sampling channel two is i, the maximum value sequence number of sampling channel three is i+2, and the maximum value sequence number of sampling channel four is i+10. Therefore, the offset of sampling channel two relative to sampling channel one is +3, which means that the leakage magnetic waveforms in the second time interval and the subsequent series of leakage magnetic waveforms in sampling channel two are uniformly offset by 3 sequence numbers. Sampling channel three has an offset of +1 relative to sampling channel one, which also means that the waveforms in the corresponding second time interval and the subsequent leakage magnetic waveforms are uniformly offset by 1 sequence number. The offset of sampling channel four relative to sampling channel one is -7, which means that the leakage magnetic waveforms in the second time interval and the subsequent series of leakage magnetic waveforms in sampling channel four are uniformly offset by 7 sequence numbers. Thus, the maximum value sequence number of the characteristic waveforms corresponding to the four sampling channels becomes i+3.

[0094] It is understandable that, for sampling channel 2, after the sequence number offset adjustment, there will inevitably be 3 missing magnetic leakage data sequence points at the left end of the second time interval, sampling channel 3 will have one missing magnetic leakage data sequence point, and sampling channel 4 will have 7 overlapping magnetic leakage data sequence points at the left end of the second time interval.

[0095] To ensure the consistency of sequence numbers across all sampling channels, the following can be further included:

[0096] Determine the maximum gap and maximum overlap intervals caused by offset in each sampling channel; cut and delete the leakage magnetic field data corresponding to the positions of the maximum gap and maximum overlap intervals in each sampling channel, including the reference sampling channel.

[0097] against Figure 4 It is clear that the largest missing area in sampling channels 1, 2, 3, and 4 is the missing magnetic leakage data area of ​​the 3 serial numbers in sampling channel 2, while the largest overlapping area is the overlapping magnetic leakage data area of ​​the 7 serial numbers in sampling channel 4. Therefore, the magnetic leakage data in sampling channels 1, 3, and 4 corresponding to the positions where missing magnetic leakage data appears in sampling channel 2 can be cut and deleted; at the same time, the magnetic leakage data in sampling channels 1, 2, 3, and 4 corresponding to the positions where overlapping magnetic leakage data appears in sampling channel 4 can also be cut and deleted.

[0098] Following the offset method described above, the corresponding waveforms between the various sampling channels within a single probe can be aligned. Based on the principle of similarity, this can be achieved... Figure 2 Using the first time interval enclosed by the large rectangle shown as a reference, the extreme points of each sampling channel are determined in the same way within the first time interval, and the offset value is determined according to the sequence number of the extreme points. The method is the same as the method of offsetting the leakage magnetic waveform between the sampling channels of a single probe, and will not be described again in this application.

[0099] It should be noted that the above offset method is used to offset and align waveform features at a point where significant misalignment occurs in each sampling channel. Each offset adjustment can adjust and align subsequent waveform features in each sampling channel to a certain extent. However, as the number of samplings increases, the sampling time deviation error gradually accumulates. Therefore, even if the initial sampling data of each sampling channel is adjusted, it cannot guarantee that the waveforms of the subsequent sampling channels will be aligned. If adjustment is required every time significant misalignment occurs in the sampling channel's magnetic flux leakage waveform, the user needs to manually mark and delineate the specific waveform multiple times. With high magnetic flux leakage data acquisition frequency and long pipelines, this obviously requires excessive manual labor. In another optional embodiment of this application, it may further include:

[0100] Based on the multiple timing segments and corresponding offsets of the leakage magnetic waveform of each sampling channel, the misalignment period and misalignment offset of the leakage magnetic waveform between each sampling channel are determined.

[0101] Based on the misalignment period and misalignment offset, the misalignment offset is adjusted once for each corresponding misalignment period of the leakage magnetic waveform of each sampling channel.

[0102] It should be noted that since the sampling deviation time between each sampling channel is generally fixed, the cumulative period and offset of significant misalignment between the leakage magnetic waveforms corresponding to each sampling channel are generally fixed. Therefore, this embodiment is based on this. After the user manually marks the specific waveforms that are significantly misaligned and completes multiple misalignment offsets, based on the determined misalignment period and misalignment offset between each sampling channel, when adjusting the alignment of the leakage magnetic waveforms between sampling channels, the misalignment period and misalignment offset can be directly used. At each interval of the misalignment period, the leakage magnetic waveform between each sampling channel can be offset once according to the misalignment offset. This achieves a series of adjustments to the leakage magnetic waveforms, ultimately obtaining leakage magnetic waveforms with aligned waveform features, providing data basis for subsequent analysis and identification of the leakage magnetic waveforms.

[0103] In summary, this application stores magnetic flux leakage data in the form of magnetic flux leakage data blocks, and only stores the sampling start time corresponding to the first magnetic flux leakage data in the block. This reduces the frequency of magnetic flux leakage data storage and the frequency of reading the data, thereby reducing the sampling delay caused by data storage in the processor of the magnetic flux leakage detector and supporting the improvement of the sampling frequency of each sampling channel. Furthermore, considering the misalignment of magnetic flux leakage data between different channels, the alignment adjustment of magnetic flux leakage data is achieved based on the magnetic flux leakage waveform, providing effective data basis for subsequent pipeline flaw detection analysis.

[0104] The data processing device for pipeline magnetic flux leakage detection provided in the embodiments of the present invention will be described below. The data processing device for pipeline magnetic flux leakage detection described below can be referred to in correspondence with the data processing method for pipeline magnetic flux leakage detection described above.

[0105] Figure 5 This is a structural block diagram of the data processing device for pipeline magnetic flux leakage detection provided in an embodiment of the present invention, with reference to... Figure 5 The data processing device for pipeline magnetic flux leakage detection may include:

[0106] The data block acquisition module 100 is used to acquire magnetic flux leakage data blocks and the sampling start time corresponding to each magnetic flux leakage data block through the magnetic flux leakage detector; wherein, the magnetic flux leakage data block is formed by continuously acquiring a preset number of magnetic flux leakage data in the same sampling channel of the magnetic flux leakage detector; and the sampling start time is the sampling time corresponding to the first magnetic flux leakage data in the magnetic flux leakage data block.

[0107] The timestamp acquisition module 200 is used to determine the sampling time corresponding to each magnetic leakage data in each magnetic leakage data block based on the sampling start time corresponding to each magnetic leakage data block;

[0108] The preliminary alignment module 300 is used to perform preliminary alignment of the magnetic flux leakage data between different sampling channels based on the sampling time.

[0109] The waveform alignment module 400 is used to form a corresponding leakage magnetic waveform from the initially aligned leakage magnetic data, and to perform feature alignment based on the waveform characteristics of the leakage magnetic waveform.

[0110] In an optional embodiment of this application, the preliminary alignment module 300 is specifically used to select a reference sampling channel among all sampling channels; set a sequence number for each leakage magnetic data in the reference sampling channel according to the corresponding sampling time; and set a sequence number for the leakage magnetic data in each sampling channel that is aligned with the sequence number of each leakage magnetic data in the reference sampling channel, so that the sequence number of the leakage magnetic data in each sampling channel is the same as the sequence number of the leakage magnetic data with the closest sampling time in the reference sampling channel.

[0111] In an optional embodiment of this application, the waveform alignment module 400 is used to visualize the leakage magnetic waveform; receive a calibration instruction to calibrate the timing segment where a specific waveform in the visualized leakage magnetic waveform is located; identify extreme points according to the specific waveform corresponding to the timing segment included in the calibration instruction, and obtain the extreme point sequence number of the specific waveform corresponding to each sampling channel; offset each sampling channel according to the offset between the extreme point sequence number of each sampling channel and the extreme point sequence number of the reference sampling channel, so that the extreme point sequence number of each sampling channel is the same as the extreme point sequence number of the reference sampling channel.

[0112] In an optional embodiment of this application, the waveform alignment module 400 is used to determine the misalignment period and misalignment offset of the leakage magnetic waveforms between the sampling channels based on the location of the timing segment and the corresponding offset of the leakage magnetic waveform of each sampling channel; and to adjust the misalignment offset once for each corresponding misalignment period based on the misalignment period and the misalignment offset.

[0113] In an optional embodiment of this application, the waveform alignment module 400 is used to offset each of the sampling channels according to a corresponding offset; determine the maximum gap interval and the maximum overlap interval in each of the sampling channels caused by the offset; and cut and delete the leakage magnetic data in each of the sampling channels, including the reference sampling channel, corresponding to the positions of the maximum gap interval and the maximum overlap interval.

[0114] The data processing device for pipeline magnetic flux leakage detection in this embodiment is used to implement the aforementioned data processing method for pipeline magnetic flux leakage detection. Therefore, the specific implementation method of the data processing device for pipeline magnetic flux leakage detection can be found in the embodiment section of the data processing method for pipeline magnetic flux leakage detection above, and will not be repeated here.

[0115] This application also provides a data processing device for pipeline magnetic flux leakage detection, characterized in that it includes a magnetic flux leakage detector and a host computer communicatively connected to the magnetic flux leakage detector; the magnetic flux leakage detector includes multiple probes, each of which includes a microprocessor, a memory and multiple sampling channels.

[0116] The microprocessor is used to store a preset number of leakage magnetic data collected by each sampling channel as a leakage magnetic data block and the sampling start time of the first leakage magnetic data in each leakage magnetic data block in the memory;

[0117] The host computer is used to obtain the magnetic flux leakage data blocks of different probes and different sampling channels and the corresponding sampling timestamps through communication connections with each of the microprocessors, and to execute the steps of the data processing method for pipeline magnetic flux leakage detection as described in any of the above claims.

[0118] The steps for data processing in pipeline magnetic flux leakage detection performed by a host computer may include:

[0119] The magnetic flux leakage data blocks obtained by the magnetic flux leakage detector and the sampling start time corresponding to each magnetic flux leakage data block; wherein, a magnetic flux leakage data block is formed by continuously collecting a preset number of magnetic flux leakage data in the same sampling channel of the magnetic flux leakage detector; the sampling start time is the sampling time corresponding to the first magnetic flux leakage data in the magnetic flux leakage data block.

[0120] Based on the sampling start time corresponding to each leakage magnetic data block, determine the sampling time corresponding to each leakage magnetic data in each leakage magnetic data block;

[0121] Preliminary alignment of magnetic flux leakage data between different sampling channels is performed based on sampling time.

[0122] The initially aligned magnetic flux leakage data is used to form corresponding magnetic flux leakage waveforms, and feature alignment is performed based on the waveform characteristics of the magnetic flux leakage waveforms.

[0123] This application also provides a computer-readable storage medium storing a computer program that is executed by a processor to implement the steps of the data processing method for internal detection of magnetic flux leakage in pipelines as described in any of the preceding claims.

[0124] The computer-readable storage medium may include random access memory (RAM), memory, read-only memory (ROM), electrically programmable ROM, electrically erasable programmable ROM, register, hard disk, removable disk, CD-ROM, or any other form of storage medium known in the art.

[0125] It should be noted that, in this document, relational terms such as "first" and "second" are used merely to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that the elements inherent in a process, method, article, or apparatus that includes a list of elements are included. 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 apparatus that includes said element. Additionally, portions of the technical solutions provided in the embodiments of this application that are consistent with the implementation principles of corresponding technical solutions in the prior art have not been described in detail to avoid excessive elaboration.

[0126] This article uses specific examples to illustrate the principles and implementation methods of the present invention. The descriptions of the above embodiments are only for the purpose of helping to understand the method and core ideas of the present invention. It should be noted that those skilled in the art can make several improvements and modifications to the present invention without departing from the principles of the present invention, and these improvements and modifications also fall within the protection scope of the claims of the present invention.

Claims

1. A data processing method for internal detection of magnetic flux leakage in pipelines, characterized in that, include: A magnetic flux leakage data block and the sampling start time corresponding to each magnetic flux leakage data block are obtained by a magnetic flux leakage detector; wherein, a magnetic flux leakage data block is formed by continuously collecting a preset number of magnetic flux leakage data in the same sampling channel of the magnetic flux leakage detector; the sampling start time is the sampling time corresponding to the first magnetic flux leakage data in the magnetic flux leakage data block. Based on the sampling start time corresponding to each of the magnetic flux leakage data blocks, the sampling time corresponding to each of the magnetic flux leakage data blocks is determined; Based on the sampling time, the leakage magnetic data between the different sampling channels are initially aligned; The initially aligned magnetic leakage data is used to form a corresponding magnetic leakage waveform, and feature alignment is performed based on the waveform characteristics of the magnetic leakage waveform. Feature alignment is performed based on the waveform characteristics of the leakage flux waveform, including: The leakage magnetic waveform is visualized. Receive a calibration command to calibrate the timing segment where a specific waveform is located in the visualized leakage magnetic waveform; Extreme point identification is performed based on the specific waveform corresponding to the time segment contained in the calibration instruction to obtain the extreme point sequence number of the specific waveform corresponding to each sampling channel; Each sampling channel is offset according to the offset between the extreme point sequence number of each sampling channel and the extreme point sequence number of the reference sampling channel, so that the extreme point sequence number of each sampling channel is the same as the extreme point sequence number of the reference sampling channel.

2. The data processing method for pipeline magnetic flux leakage detection as described in claim 1, characterized in that, Based on the sampling time, preliminary alignment of the leakage magnetic data between different sampling channels is performed, including: Select a reference sampling channel from all sampling channels; Each leakage magnetic field data in the reference sampling channel is assigned a sequence number according to its corresponding sampling time; The leakage magnetic field data of each sampling channel is set with a sequence number that is aligned with the sequence number of each leakage magnetic field data in the reference sampling channel, so that the sequence number of the leakage magnetic field data in each sampling channel is the same as the sequence number of the leakage magnetic field data with the closest sampling time in the reference sampling channel.

3. The data processing method for pipeline magnetic flux leakage detection as described in claim 1, characterized in that, After aligning the extreme point sequence numbers of each of the sampling channels, the method further includes: Based on the location of the timing segment and the corresponding offset of the leakage magnetic waveform of each sampling channel, the misalignment period and misalignment offset of the leakage magnetic waveform between each sampling channel are determined. Based on the misalignment period and the misalignment offset, the leakage magnetic waveform of each sampling channel is adjusted once every corresponding misalignment period.

4. The data processing method for pipeline magnetic flux leakage detection as described in claim 1, characterized in that, Offset each sampling channel based on the offset between the extreme point sequence number of each sampling channel and the extreme point sequence number of the reference sampling channel, including: Each of the sampling channels is offset according to its corresponding offset; Determine the maximum gap interval and the maximum overlap interval caused by offset in each of the sampling channels; The magnetic flux leakage data corresponding to the positions of the maximum gap interval and the maximum overlap interval in each of the sampling channels, including the reference sampling channel, are cut and deleted.

5. A data processing device for internal detection of magnetic flux leakage in pipelines, characterized in that, include: A data block acquisition module is used to acquire magnetic flux leakage data blocks and the sampling start time corresponding to each magnetic flux leakage data block through a magnetic flux leakage detector; wherein, a magnetic flux leakage data block is formed by continuously acquiring a preset number of magnetic flux leakage data in the same sampling channel of the magnetic flux leakage detector; and the sampling start time is the sampling time corresponding to the first magnetic flux leakage data in the magnetic flux leakage data block. The timestamp acquisition module is used to determine the sampling time corresponding to each magnetic leakage data in each magnetic leakage data block based on the sampling start time corresponding to each magnetic leakage data block; A preliminary alignment module is used to perform preliminary alignment of the magnetic flux leakage data between different sampling channels based on the sampling time. The waveform alignment module is used to form a corresponding leakage magnetic waveform from the initially aligned leakage magnetic data, and to perform feature alignment based on the waveform characteristics of the leakage magnetic waveform. The waveform alignment module is used to visualize the leakage magnetic waveform; receive a calibration command to calibrate the timing segment where a specific waveform in the visualized leakage magnetic waveform is located; identify extreme points according to the specific waveform corresponding to the timing segment included in the calibration command, and obtain the extreme point sequence number of the specific waveform corresponding to each sampling channel; offset each sampling channel according to the offset between the extreme point sequence number of each sampling channel and the extreme point sequence number of the reference sampling channel, so that the extreme point sequence number of each sampling channel is the same as the extreme point sequence number of the reference sampling channel.

6. The data processing device for pipeline magnetic flux leakage detection as described in claim 5, characterized in that, The preliminary alignment module is specifically used to select a reference sampling channel among all sampling channels; set a sequence number for each leakage magnetic data in the reference sampling channel according to the corresponding sampling time; and set a sequence number for the leakage magnetic data in each sampling channel that is aligned with the sequence number of each leakage magnetic data in the reference sampling channel, so that the sequence number of the leakage magnetic data in each sampling channel is the same as the leakage magnetic data in the reference sampling channel with the closest sampling time.

7. A data processing device for internal detection of magnetic flux leakage in pipelines, characterized in that, The system includes a magnetic flux leakage detector and a host computer that is communicatively connected to the magnetic flux leakage detector; the magnetic flux leakage detector includes multiple probes, each of which includes a microprocessor, a memory and multiple sampling channels. The microprocessor is used to store a preset number of leakage magnetic data collected by each sampling channel as a leakage magnetic data block and the sampling start time of the first leakage magnetic data in each leakage magnetic data block in the memory; The host computer is used to obtain the magnetic flux leakage data blocks of different probes and different sampling channels and the corresponding sampling timestamps through communication connections with each of the microprocessors, and to execute the steps of the data processing method for internal detection of magnetic flux leakage in pipelines as described in any one of claims 1 to 4.

8. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that is executed by a processor to implement the steps of the data processing method for internal detection of magnetic flux leakage in pipelines as described in any one of claims 1 to 4.

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