Pipeline machining production line quality control system and method

Abstract

The invention provides a pipeline processing production line quality control system and method, and the system comprises a processing module which comprises at least two sub-processing modules and is used for processing a to-be-processed pipeline; the detection module is used for determining pipeline parameters of the processed pipeline and judging whether the processed pipeline is qualified or not; the control module is used for obtaining the pipeline parameters and the qualified rate of the pipelines machined by the target sub-machining module in the preset period; and determining a target optimization module as the target sub-processing module and / or the detection module according to the pipeline parameters and the qualified rate so as to control the target optimization module to execute corresponding optimization operation. The problem of low quality control efficiency of a processing production line in the prior art is solved.

Description

Technical Field

[0001] The present invention relates to the field related to pipeline processing, and specifically provides a pipeline processing production line quality control system and method. Background Art

[0002] The various functional modules of a vehicle system are connected through pipelines, and the quality of these pipelines is closely linked to the proper functioning of all relevant vehicle systems. Currently, rail transit vehicle pipelines are numerous and numerous. Traditional manual spot checks to control pipeline quality are inefficient and prone to errors. Furthermore, manual quality control of production lines is labor-intensive and cumbersome, making it difficult to comprehensively analyze all pipeline quality data and quickly identify components requiring optimization, reducing quality control efficiency. Summary of the Invention

[0003] The technical problem to be solved by the present invention is to overcome the shortcomings of the existing technology. The purpose is to provide a pipeline processing production line quality control system and method, which automatically detects pipeline parameters through a detection module, analyzes pipeline parameters and qualification rate through a control module, determines the target optimization module as the target sub-processing module and / or detection module, considers the reasons affecting pipeline quality from multiple aspects, and thus accurately and quickly locks the target optimization module, and then performs corresponding optimization operations, controls pipeline processing quality, and improves management and control efficiency.

[0004] The first invention object of the present invention is to provide a pipe processing production line quality control system, which adopts the following technical solutions:

[0005] A processing module, comprising at least two sub-processing modules, for processing the pipeline to be processed;

[0006] A detection module, used to determine pipeline parameters of the processed pipeline and judge whether the processed pipeline is qualified;

[0007] The control module is used to obtain the pipeline parameters and pass rate of the pipeline processed by the target sub-processing module within a preset period; based on the pipeline parameters and the pass rate, determine that the target optimization module is the target sub-processing module and / or the detection module to control the target optimization module to perform corresponding optimization operations.

[0008] The second object of the present invention is to provide a method for controlling the quality of a pipe processing production line, which is applied to the above-mentioned pipe processing production line quality control system and adopts the following technical solutions:

[0009] Obtaining pipeline parameters and qualification rates of pipelines processed within a preset cycle of the target sub-processing module;

[0010] According to the pipeline parameters and the qualified rate, the target optimization module is determined to be the target sub-processing module and / or the detection module, so as to control the target optimization module to perform corresponding optimization operations.

[0011] In summary, the present invention provides a pipeline processing production line quality control system and method, which has the following beneficial effects compared with the prior art:

[0012] The detection module automatically detects pipeline parameters, and the control module analyzes pipeline parameters and qualified rates, comprehensively determines the target optimization module as the target sub-processing module and / or detection module and / or process design module, and considers the factors affecting the pipeline processing quality and stability from multiple aspects, so as to accurately and quickly lock the module to be optimized, and then perform the corresponding optimization operation, update the parameters of the target optimization module, control the pipeline processing quality, and improve the management and control efficiency; in addition, through the cooperation of the laser marking module, the processing module and the detection module, the quality information can be traced at any time, which facilitates the information statistics of pipeline processing and makes pipeline management more convenient, while providing data support for the control module to analyze and determine the target optimization module. BRIEF DESCRIPTION OF THE DRAWINGS

[0013] The accompanying drawings, as part of this disclosure, are intended to provide a further understanding of the disclosure. The exemplary embodiments of the disclosure and their descriptions are intended to explain the disclosure and do not constitute undue limitations thereon. Obviously, the drawings described below are merely examples, and those skilled in the art can derive other drawings based on these drawings without inventive effort.

[0014] In the attached figure:

[0015] Figure 1 This is a flow chart of a pipeline processing production line quality control method provided by the present invention;

[0016] Figure 2 This is an interactive flow chart of a pipeline processing production line quality control system provided by the present invention;

[0017] Figure 3 This is a design drawing of a pipeline marker provided by the present invention;

[0018] Figure 4 This is a design drawing of pipeline coding provided by the present invention;

[0019] Figure 5 This is a flow chart of another pipeline processing production line quality control method provided by the present invention.

[0020] It should be noted that these drawings and textual descriptions are not intended to limit the conceptual scope of the present invention in any way, but rather to illustrate the concept of the present invention for those skilled in the art by referring to specific embodiments. DETAILED DESCRIPTION

[0021] In order to enable those skilled in the art to better understand the present invention, the following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments in the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts should fall within the scope of protection of this application.

[0022] It should be noted that the terms "first", "second", etc. in the specification and claims of the present application and the above-mentioned drawings are used to distinguish similar objects and are not necessarily used to describe a specific order or sequential order. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments of the present application described herein can be implemented in a sequence other than those illustrated or described herein. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device comprising a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0023] The present invention provides a pipeline processing production line quality control system, comprising: a processing module, including at least two sub-processing modules, for processing the pipeline to be processed; a detection module, for determining the pipeline parameters of the processed pipeline and judging whether the processed pipeline is qualified; a control module, for obtaining the pipeline parameters and the pass rate of the pipeline processed by the target sub-processing module within a preset period; according to the pipeline parameters and the pass rate, determining the target optimization module as the target sub-processing module and / or the detection module, so as to control the target optimization module to perform corresponding optimization operations.

[0024] like Figure 1 As shown, in this embodiment, the sub-processing module may include a cutting module, a chamfering module, a cleaning module, and a pipe bending module. The cutting module is used to cut long pipes into single pipes according to the designed length. Accordingly, after the cutting module is processed, it is necessary to detect whether the pipe length meets the designed length; after cutting, there may be burrs on the cut surface. The chamfering module is used to remove burrs, flash, etc. on the pipe end after cutting. Therefore, after the chamfering module is processed, it is necessary to detect whether there are burrs on the pipe end; the cleaning module is used to clean the inner and outer pipe walls of the pipe. Therefore, after the cleaning module is cleaned, it is necessary to detect the cleanliness of the pipe wall to determine whether the cleanliness meets the requirements; the pipe bending module is used to bend straight pipes into U-shaped, S-shaped, etc. bends. Therefore, after the pipe bending module is processed, it is necessary to detect the bend angle to determine whether the bending angle error exceeds the range.

[0025] In addition, if Figure 1As shown, the pipe processing production line quality control system also includes a loading module, which is used to move the pipe to the processing position. Before loading, pipe information must be inspected. This information includes pipe material, specifications, length, cutting length, bending procedures, and other information. Accordingly, the pipe processing production line quality monitoring system also includes a data storage module for storing pipe information.

[0026] The laser marking module is used to generate a pipeline mark according to the above pipeline information, and to engrave the pipeline mark on the pipeline by laser engraving, so that the subsequent processing submodule can obtain the pipeline information of the pipeline and process the pipeline according to the pipeline information.

[0027] According to the above embodiment, there are multiple inspection modules, each corresponding to a sub-processing module. Pipeline parameters may include pipeline length, number of burrs, cleanliness, and bend angle. The inspection module compares the pipeline parameters with standard parameters to determine whether the processed pipeline meets the requirements.

[0028] Specifically, the target sub-processing module is the sub-processing module and the sub-processing module corresponding to the inspection module for this quality control. The target sub-processing module can be set manually or determined based on factors such as the inspection cycle.

[0029] Specifically, the preset period can be set according to actual application data. Assuming that the preset period is 12 hours, the pipeline parameters and pass rates of the pipelines processed by the target sub-processing module in the past 12 hours are obtained as reference data.

[0030] The pass rate can be used to intuitively determine whether a production line's current quality level meets expectations. For example, if the preset pass rate is greater than or equal to 99%, a pass rate of 98% indicates quality issues on the processing line. However, the pass rate cannot determine whether the processing quality of a processing line is stable. For example, if a production line experiences significant fluctuations, but the samples tested by the inspection module happen to have a high pass rate, this could mask potential risks. For example, if two production lines have the same pass rate—one passing due to process stability, the other passing due to loose tolerances—they may have different actual capabilities. Therefore, relying solely on the pass rate cannot determine whether the processing quality is stable.

[0031] Pipeline parameters can be used to analyze the dispersion and mean shift of process data, quantitatively assessing production line stability. However, analyzing production line stability based solely on pipeline parameters can lead to the situation where two production lines with the same stability may appear stable due to a high rate of substandard products, while another may appear stable due to a high rate of qualified products. Therefore, a comprehensive assessment based on pipeline parameters and pass rates is necessary.

[0032] Furthermore, if the processed pipes within the preset cycle fail to meet the standards, or if all pipes meet the standards but the pipe parameters show unstable or inaccurate processing quality, this could be due to a fault in the sub-processing module, a detection error in the corresponding detection module, or an overly idealized standard data for the sub-processing module that is difficult to achieve in actual production. Therefore, it is necessary to identify the problem module so that targeted optimization can be carried out, and quality control can be implemented on the pipe processing production line to improve pipe quality and work efficiency.

[0033] like Figure 2 As shown in the figure, the quality monitoring module (also known as the control module) determines whether the pipeline is qualified based on the test results fed back by the inspection module. After each module performs the optimization operation, it will pass the updated data to other modules, allowing each module to perform quality control on the processing line according to the new quality data / quality standards.

[0034] Furthermore, it also includes a process design module for standard parameters corresponding to the target sub-processing module; the detection module is also used to determine the pass rate within the preset period of the target sub-processing module based on the standard parameters and the pipeline parameters of the pipeline processed within the preset period of the target sub-processing module.

[0035] like Figure 2 As shown, the process design module constructs a digital model of the processing module to determine quality data, which includes design values ​​and process values. Design values ​​are ideal parameter values ​​pre-set based on product functional requirements, theoretical calculations, or industry standards. To account for the discrepancy between ideal and actual production conditions, design values ​​have an adjustable tolerance range. Process values, on the other hand, are program parameters used during actual production and processing. To account for equipment wear during use, process values ​​have adjustable process compensation parameters. For example, assume the ideal straight pipe length requirement is 1000mm ± 5mm, with a tolerance of ± 5mm. The digital model translates these into process values ​​for the cutting module: a cutting speed of 100mm / min ± 0.5mm / min, a feed pressure of 0.5MPa ± 0.05MPa, and process compensation parameters of ± 0.5mm / min and ± 0.05MPa. If the processed pipe length is 1001mm, the pipe is considered qualified; if the processed pipe length is 1007mm, the pipe is considered unqualified.

[0036] Specifically, the standard parameters are the above-mentioned design values. According to the above example, the standard parameters are (995, 1005).

[0037] like Figure 2As shown, in this embodiment, the design values ​​include length, angle, and reduction rate; the process values ​​include length, angle, and reduction rate. The length process compensation parameter is ±1, and the angle process compensation parameter is ±△. The process design module feeds quality data back to the control module, which then feeds the quality data back to the processing module and the inspection module as quality standards.

[0038] In addition, if the difference between the pipeline parameters and the standard parameters is too large, it may be that the pipeline processed by the processing equipment using the process values ​​cannot meet the design value standards. In this case, the process design module is the target optimization module, and the process values ​​of the process design module need to be adjusted.

[0039] Furthermore, the control module is also used to, if the pass rate is less than a preset pass rate, determine a target optimization module according to the pass rate; and determine an optimization operation corresponding to the target optimization module according to pipeline parameters of unqualified pipelines.

[0040] Specifically, the preset pass rate is determined based on actual operating conditions. Assuming a preset pass rate of 98%, a pass rate below 98% indicates quality issues with the pipe processing line. The pass rate varies depending on the module. For example, if a large number of pipes fail, it could be due to a fault in the inspection module, resulting in inaccurate measurement results and requiring metrological calibration. If a small number of pipes fail, it could be due to a decrease in the precision of the sub-processing module, such as tool wear leading to burrs on the pipe ends, requiring inspection and maintenance of the sub-processing module.

[0041] Therefore, by analyzing the pass rate, we can quickly locate the root cause of the problem, thereby carrying out targeted quality control and improving work efficiency.

[0042] Furthermore, the control module is also used to, if the pass rate is less than the preset pass rate and greater than the first pass rate, determine that the target optimization module is a process design module; if the pass rate is less than the first pass rate and greater than the second pass rate, determine that the target optimization module is a target sub-processing module; if the pass rate is less than the second pass rate, determine that the target optimization module is a detection module corresponding to the target sub-processing module.

[0043] Specifically, the preset pass rate is greater than the first pass rate, and the first pass rate is greater than the second pass rate. Specific values ​​of the first pass rate and the second pass rate are determined according to actual working conditions.

[0044] If the pass rate is less than the preset pass rate and greater than the first pass rate, it means that only the pipeline parameters of individual pipelines do not meet the standards. As an example, assume that the preset pass rate is 98%, the first pass rate is 95%, and the second pass rate is 80%. If the pass rate is 97%, it means that the pipeline pass rate is close to the preset pass rate, but there are individual pipelines that do not meet the standards. According to the above, pipeline processing that meets standard parameters is the effect that can be achieved under ideal conditions. In the actual processing and production process, a variety of unpredictable, small and accidental factors may work together to cause the processed pipeline to not meet the ideal state. For example, fluctuations in workpiece thermal deformation, changes in coolant flow, etc. This type of deviation has no obvious regularity and is difficult to completely eliminate with a single factor. However, the occurrence of this situation can be reduced by adjusting the process compensation parameters of the process design module, that is, adjusting the process values. It is also possible to adjust the tolerance range of the process design module, that is, adjust the design values.

[0045] If the pass rate is less than the first pass rate and greater than the second pass rate, it means that a small number of pipelines have pipeline parameters that do not meet the standards. According to the above example, the pass rate can be 90%. At this time, the appearance of unqualified pipelines is not accidental, and the number is small. It may be that the equipment hardware and operating status of the processing module are not good, resulting in some pipelines being unqualified. For example, the tool is worn and not replaced in time, the cutting edge becomes blunt, resulting in the offset of the cutting size, the spindle bearing is damaged or poorly lubricated, resulting in rough processing surface and other problems. Figure 2 As shown in the figure, if there are burrs on the ends of three consecutive pipes, or if the length of five consecutive pipes is unqualified, it may be caused by wear of the chamfering machine and peeling machine tools. In this case, these problems can be discovered and solved in a timely manner by replacing parts, increasing inspection frequency, and adjusting maintenance intervals.

[0046] If the pass rate is less than the second pass rate, it means that the pipeline parameters of a large number of pipelines do not meet the standards. According to the above example, the pass rate can be 60%. The accuracy and stability of the testing equipment directly affect the judgment of whether the product is qualified or not. Its own problems may cause qualified products to be judged as unqualified, or unqualified products to be judged as qualified, which will seriously affect the statistical pass rate. Figure 2 As shown, Figure 2 Both the cleanliness inspection and the bend inspection use cameras. If there are errors in the camera focal length, camera position, and reference target, all pipes inspected by the inspection equipment may fail. In this case, the inspection module status and equipment accuracy need to be checked and calibrated.

[0047] It should be noted that if a processing module experiences a serious failure, even if the detection module's accuracy and stability are good, a large number of pipelines will still fail. Therefore, after determining and adjusting the target optimization module, it is necessary to re-inspect the quality of the pipelines processed by the target sub-processing module to achieve closed-loop control of the entire process, reduce the possibility of misjudgment, and minimize losses.

[0048] Furthermore, the control module is also used to determine the process capability index based on the pipeline parameters if the pass rate is greater than the preset pass rate; and determine the target optimization module as a process design module and / or a target sub-processing module based on the process capability index.

[0049] Based on the above, if the pass rate is greater than the preset pass rate, it indicates that the pipe quality of the processing line meets the requirements and the inspection module is operating normally. At this point, it is necessary to consider the stability of the processing line. That is, to determine whether the pass is due to process stability or due to loose tolerance range. This can identify quality risks in advance and optimize fluctuations or deviations in a targeted manner to achieve stable production of the processing line.

[0050] Specifically, the Process Capability Index (CPK) is an important indicator that measures whether a production process can stably produce products that meet specification requirements. The preset range is determined based on actual operating conditions. As an example, the preset range is (1.33, 1.67). If the CPK is greater than 1.67, it means that the CPK is too high, there is excess production capacity, and the tolerance range can be relaxed. For example, the process can be simplified and the inspection frequency can be reduced. If the CPK is less than 1.33, it means that the CPK is too low, the capacity is insufficient, and defective products may occur. It is necessary to optimize the process and narrow the tolerance range.

[0051] The target sub-processing module uses the process values ​​from the process design module as a reference for processing the pipeline, thereby producing pipeline parts close to the designed values. In one embodiment, if the CPK indicates that the production quality of the processing line fluctuates, it may be that the process values ​​do not match the actual production capacity, requiring adjustment of the process values. Accordingly, the processing program parameters of the sub-processing module will be adjusted accordingly. The target optimization module is composed of the target sub-processing module and the process design module.

[0052] As an example, assume that the target sub-processing module is a pipe bending module, and the process values ​​include a bending angle of 90.5° and a pipe diameter of 50.2mm. After the pipe bending module has been used for half a year, the mean bending angle shifts due to mold wear: actual measurements show that when produced according to the original process settings, the mean bending angle drops to 90.2°, and the fluctuation increases. Even if the pipes produced at this time are still qualified, it will cause subsequent quality problems. The process value of the bending angle is increased from 90.5° to 90.8° to compensate for the angle reduction caused by equipment wear. The processing program parameters executed by the corresponding pipe bending module are adjusted.

[0053] In another example, if the CPK indicates fluctuations in production quality on a processing line, this could be due to an inappropriate tolerance design. For example, the standard parameter is 10±0.03mm, but to improve production efficiency, the actual control range is relaxed to 10±0.05mm. The process tolerance is now 0.1mm, wider than the design tolerance, potentially resulting in a drop in yield. In this case, the design value, or standard parameter, needs to be adjusted, and the target optimization module is the process design module.

[0054] In another embodiment, CPK shows that the production quality of the processing line fluctuates, which may be due to wear and tear of the sub-processing module, looseness, etc. In this case, the sub-processing module needs to be inspected and maintained more carefully, and the target optimization module is the target sub-processing module.

[0055] Furthermore, the control module is also used to, if the target optimization module is a process design module, determine the corresponding optimization operation as adjusting the standard parameters of the process design module according to the pipeline parameters; if the target optimization module is a target sub-processing module, determine the corresponding optimization operation as adjusting the maintenance cycle and / or inspection frequency of the target sub-processing module.

[0056] According to the above, if the target optimization module is the process design module and CPK is too low, the optimization operation is to narrow the tolerance range according to the pipeline parameters; if the target optimization module is the process design module and CPK is too high, the optimization operation is to expand the tolerance range according to the pipeline parameters.

[0057] If the target optimization module is the target sub-processing module and the CPK is too low, the optimization operation is to extend the block maintenance cycle of the target sub-processing module and / or reduce the inspection frequency of the target sub-processing module; if the target optimization module is the target sub-processing module and the CPK is too high, the optimization operation is to shorten the block maintenance cycle of the target sub-processing module and / or increase the inspection frequency of the target sub-processing module.

[0058] like Figure 1 As shown in , the target sub-processing module is inspected for equipment accuracy, and the equipment accuracy to be inspected for different sub-processing modules is different. Figure 2As shown, when the sub-processing module is a rotary cutter, the equipment accuracy to be checked includes the feed mechanism accuracy, spindle speed, and tool life; when the sub-processing module is a chamfering machine, the equipment accuracy to be checked includes the feed amount, spindle speed, and tool life; when the sub-processing module is a cleaning machine, the cleaning machine uses a dedicated pneumatic gun to fire sponge bullets into the pipe to be cleaned. The sponge bullets, relying on their hardness and elasticity, create friction with the inner wall of the pipe, thereby removing dirt and sediment within the pipe. Therefore, the equipment accuracy to be checked includes the bullet diameter, cleaning air pressure, and the equipment accuracy of the servo motor; when the sub-processing module is a pipe bender, the equipment accuracy to be checked includes the bending speed, feed amount, and mold status. The inspection and maintenance cycle of the target sub-processing module can be the same or different.

[0059] Furthermore, it also includes a laser marking module for engraving a pipeline marking on the pipeline to be processed; the processing module is specifically used to scan the pipeline marking of the pipeline to be processed, determine the target processing program of the pipeline to be processed, and process the pipeline to be processed according to the target processing program.

[0060] In this embodiment, the pipeline identifier can be a QR code, which provides pipeline information of the pipeline after being scanned. According to the above, the pipeline information includes the target processing program.

[0061] If the sub-processing modules include a cutting module, a chamfering module, a cleaning module, and a pipe bending module, then the target processing program includes a target cutting program, a target chamfering program, a target cleaning program, and a target pipe bending program. Different target processing programs correspond to different processing program parameters to meet various pipeline production requirements. These processing program parameters are the process values ​​in the process design module mentioned above.

[0062] Specifically, different target cutting programs correspond to different cutting lengths, different target chamfering programs correspond to different chamfer angles, different target cleaning programs correspond to different cleaning times, and different target bending programs correspond to different bending angles. Therefore, before pipe machining, the standard parameters for the pipe after machining—that is, the design values—are determined, along with the target machining program required to achieve them. This allows the target sub-machining module to machine the pipe according to the target machining program, resulting in a pipe part that meets the requirements.

[0063] like Figure 3 As shown, Figure 3It is a design drawing for pipeline identification. In this embodiment, field 1 is the production item number of the day, which occupies 4 characters; field 2 is the production column number of the day's production item, which occupies 3 characters; field 3: the vehicle number corresponding to the production column number of the day's production item, which occupies 2 characters; field 4 is the material code of the production, which occupies 11 characters; the material code is used to find pipeline information in the data storage module; field 5 is the manufacturer information of the pipeline raw materials, which occupies 1 character; field 6 is the raw material batch information, which occupies 2 characters. The batch information is recorded and stored in the warehouse management system when the pipeline raw materials are put into storage. When the pipes are shipped out for pipeline processing, the batch information is sent from the warehouse management system to the laser identification module, and the generated QR code is engraved on the pipeline. In this way, by scanning the QR code, not only can the pipeline information be found, but the entire life cycle of the pipeline can also be traced to achieve digital management.

[0064] In another embodiment, the laser marking module is also used to engrave pipeline codes on the pipeline. Figure 4 As shown, Figure 4 This is a coded pipeline design. In this example, Field 1 is the vehicle number of the specific project to which the pipeline belongs; Field 2 is the vehicle category number; Field 3 is the sub-item drawing number corresponding to the specific category; and Field 4 is the part number corresponding to the assembly drawing number to which the pipeline belongs. Engraving the pipeline code on the pipeline facilitates quick location and identification during vehicle assembly, as well as quick identification of similar pipelines during vehicle maintenance and replacement, improving work efficiency.

[0065] Specifically, before processing the pipeline to be processed according to the target processing program, the processing module is also used to obtain the pipeline length of the pipeline to be processed, compare the pipeline length with the preset length, and if the pipeline length is consistent with the preset length, move the pipeline to be processed to the processing position.

[0066] Furthermore, the detection module is specifically used to scan the pipeline identification of the pipeline to be detected and determine the standard parameters corresponding to the pipeline to be detected; perform quality inspection on the pipeline to be detected and determine the pipeline parameters of the pipeline to be detected; if the pipeline parameters are consistent with the standard parameters, the pipeline to be detected is judged to be qualified.

[0067] like Figure 1 As shown, different sub-processing modules perform different processing operations on the pipeline. Accordingly, the detection module detects different data and obtains different standard parameters. In this embodiment, when the sub-processing module is a cutting module, it detects pipeline length; when the sub-processing module is a chamfering module, it detects the number of burrs; when the sub-processing module is a cleaning module, it detects the cleanliness of the pipe wall; and when the sub-processing module is a bending module, it detects the bend angle. It should be noted that equipment accuracy testing and pipeline parameter testing can be performed simultaneously or separately.

[0068] like Figure 2 As shown, the length of the pipeline can be detected using a grating ruler under the control of a servo mechanism. Pipeline length can also be measured using a laser distance measuring device or a visual inspection device, avoiding the problem of large manual measurement errors, speeding up the inspection, and improving work efficiency.

[0069] Visual inspection devices, such as industrial cameras, can be used to inspect pipe wall cleanliness and bend angles.

[0070] Furthermore, the pipeline parameters include at least pipeline length, bend angle and pipe wall cleanliness; the detection module includes a laser detection module and a visual detection module; the laser detection module is used to detect the pipeline length; the visual detection module is used to detect the bend angle and the pipe wall cleanliness.

[0071] According to the above, if the visual inspection module is an industrial camera, when inspecting the cleanliness of the pipe wall, the industrial camera takes a picture of the cleaned pipe wall, and detects whether there is any residue on the pipe wall based on the photograph. If there is no residue, it is judged that the cleaning is qualified.

[0072] When detecting the angle of a bend, the camera is used to capture the projection image of the bend, extract the edge contour of the bend, and calculate the angle between the line segments. Alternatively, a 3D vision device is used to obtain point cloud data, fit the spatial curve, and calculate the angle.

[0073] According to the above, pipeline information needs to be detected before loading the pipeline, so the laser detection module and the visual detection module are also used to detect the pipeline information.

[0074] An embodiment of the present invention also provides a pipeline processing production line quality control method, which is applied to the above-mentioned pipeline processing production line quality control system, including: obtaining the pipeline parameters and pass rate of the pipeline processed by the target sub-processing module within a preset period; based on the pipeline parameters and the pass rate, determining the target optimization module as the target sub-processing module and / or the detection module, so as to control the target optimization module to perform corresponding optimization operations.

[0075] like Figure 5 As shown, Figure 5 This is a flow chart of a pipeline processing production line quality control method provided by the present invention.

[0076] In another embodiment, based on the pipeline parameters and the pass rate, the target optimization module is determined to be the target sub-processing module and / or the detection module, specifically including: if the pass rate is less than the preset pass rate, the target optimization module is determined according to the pass rate, and the optimization operation corresponding to the target optimization module is determined according to the pipeline parameters of the unqualified pipeline; if the pass rate is greater than the preset pass rate, the process capability index is determined according to the pipeline parameters; based on the process capability index, the target optimization module is determined to be the process design module and / or the target sub-processing module.

[0077] Determining a target optimization module according to the pass rate specifically includes: if the pass rate is less than the preset pass rate and greater than the first pass rate, determining the target optimization module as a process design module; if the pass rate is less than the first pass rate and greater than the second pass rate, determining the target optimization module as a target sub-processing module; if the pass rate is less than the second pass rate, determining the target optimization module as a detection module corresponding to the target sub-processing module.

[0078] After determining the target optimization module, it also includes: if the target optimization module is a process design module, determining the corresponding optimization operation is to adjust the standard parameters of the process design module according to the pipeline parameters; if the target optimization module is a target sub-processing module, determining the corresponding optimization operation is to adjust the maintenance cycle and / or inspection frequency of the target sub-processing module.

[0079] In summary, the present invention provides a pipeline processing production line quality control system and method, which has the following beneficial effects compared with the prior art:

[0080] The detection module automatically detects pipeline parameters, and the control module analyzes pipeline parameters and qualified rates, comprehensively determines the target optimization module as the target sub-processing module and / or detection module and / or process design module, and considers the factors affecting the pipeline processing quality and stability from multiple aspects, so as to accurately and quickly lock the module to be optimized, and then perform the corresponding optimization operation, update the parameters of the target optimization module, control the pipeline processing quality, and improve the management and control efficiency; in addition, through the cooperation of the laser marking module, the processing module and the detection module, the quality information can be traced at any time, which facilitates the information statistics of pipeline processing and makes pipeline management more convenient, while providing data support for the control module to analyze and determine the target optimization module.

[0081] The above description is merely a preferred embodiment of the present invention and does not constitute any form of limitation to the present invention. Although the present invention has been disclosed as above in terms of a preferred embodiment, it is not intended to limit the present invention. Any technician familiar with this patent can make slight changes or modifications to equivalent embodiments of equivalent changes using the above-mentioned technical contents without departing from the scope of the technical solution of the present invention. The implementation schemes in the above-mentioned embodiments can also be further combined or replaced. However, any simple modifications, equivalent changes and modifications made to the above-mentioned embodiments based on the technical essence of the present invention without departing from the content of the technical solution of the present invention are still within the scope of the solution of the present invention.

Claims

1. A quality monitoring system for a pipeline processing production line, characterized in that: include, A processing module, comprising at least two sub-processing modules, for processing the pipeline to be processed; A detection module, used to determine pipeline parameters of the processed pipeline and judge whether the processed pipeline is qualified; The control module is used to obtain the pipeline parameters and pass rate of the pipeline processed by the target sub-processing module within a preset period; based on the pipeline parameters and the pass rate, determine that the target optimization module is the target sub-processing module and / or the detection module to control the target optimization module to perform corresponding optimization operations.

2. The pipe processing production line quality control system according to claim 1, characterized in that: Also includes, Process design module, which is used for standard parameters corresponding to target sub-processing modules; The detection module is further configured to determine a qualified rate within a preset period of the target sub-processing module based on the standard parameters and pipeline parameters of the pipeline processed within a preset period of the target sub-processing module.

3. The pipe processing production line quality control system according to claim 1 or 2, characterized in that: The control module is further configured to: If the qualified rate is less than the preset qualified rate, determining the target optimization module according to the qualified rate; According to the pipeline parameters of the unqualified pipeline, the optimization operation corresponding to the target optimization module is determined.

4. The pipe processing production line quality control system according to claim 3, characterized in that: The control module is further configured to: If the qualified rate is less than the preset qualified rate and greater than the first qualified rate, determining that the target optimization module is a process design module; If the qualified rate is less than the first qualified rate and greater than the second qualified rate, determining the target optimization module as the target sub-processing module; If the qualified rate is less than the second qualified rate, it is determined that the target optimization module is the detection module corresponding to the target sub-processing module.

5. The pipe processing production line quality control system according to claim 1 or 2, characterized in that: The control module is further configured to: If the qualified rate is greater than a preset qualified rate, determining a process capability index according to the pipeline parameters; According to the process capability index, the target optimization module is determined to be a process design module and / or a target sub-processing module.

6. The pipe processing production line quality control system according to claim 5, characterized in that: The control module is further configured to: If the target optimization module is a process design module, determining the corresponding optimization operation is to adjust the standard parameters of the process design module according to the pipeline parameters; If the target optimization module is a target sub-processing module, then determining the corresponding optimization operation is to adjust the maintenance period and / or inspection frequency of the target sub-processing module.

7. The pipe processing production line quality control system according to claim 1, characterized in that: It also includes a laser marking module for engraving pipeline markings on the pipeline to be processed; The processing module is specifically used to: Scanning the pipeline identification of the pipeline to be processed to determine the target processing program of the pipeline to be processed; The pipeline to be processed is processed according to the target processing program.

8. The pipe processing production line quality control system according to claim 7, characterized in that: The detection module is specifically used to: Scanning the pipeline identification of the pipeline to be tested to determine the standard parameters corresponding to the pipeline to be tested; Performing quality inspection on the pipeline to be inspected to determine pipeline parameters of the pipeline to be inspected; If the pipeline parameters are consistent with the standard parameters, the pipeline to be tested is judged to be qualified.

9. The pipe processing production line quality control system according to claim 8, characterized in that: The pipeline parameters include at least pipeline length, bend angle and pipe wall cleanliness; The detection module includes a laser detection module and a visual detection module; The laser detection module is used to detect the length of the pipeline; The visual inspection module is used to detect the pipe bending angle and the cleanliness of the pipe wall.

10. A pipe processing production line quality control method, applied to the pipe processing production line quality control system according to any one of claims 1 to 9, characterized in that: include: Obtaining pipeline parameters and qualification rates of pipelines processed within a preset cycle of the target sub-processing module; According to the pipeline parameters and the qualified rate, the target optimization module is determined to be the target sub-processing module and / or the detection module, so as to control the target optimization module to perform corresponding optimization operations.

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