Process monitoring method and equipment based on plastic liner welding and medium

Abstract

The invention discloses a process monitoring method and device based on plastic liner welding and a medium, belongs to the technical field of plastic welding processes, and aims to solve the problems that in an existing plastic liner welding process, due to the actual deviation factor of a welding seam, a certain error influence is easily caused on a welded whole plastic liner, and the welding quality of the whole plastic liner is influenced. And therefore, the qualified rate of products is reduced. The method comprises the following steps: carrying out ultrasonic detection treatment under related phase-controlled radar on a to-be-detected welding seam area of the welded plastic liner to obtain ultrasonic data of the welding seam area; performing defect evaluation processing on the ultrasonic data of the welding seam area to obtain a welding seam ultrasonic evaluation score of the welding seam area; if the weld joint ultrasonic evaluation score is greater than a first standard score, performing image calculation processing on the weld joint area under a related edge pixel slope, and determining a weld joint flatness evaluation score; and if the weld joint flatness evaluation score is greater than a second standard score, performing all-directional monitoring on the overall configuration of the plastic liner to obtain an overall configuration evaluation score.

Description

Technical Field

[0001] The present application relates to the technical field of plastic welding processes, and in particular to a process monitoring method, equipment, and medium based on plastic liner welding. Background Art

[0002] In the existing plastic liner welding process, a plastic (PA) liner welding device using an infrared lamp as a heating source can be used to weld two incomplete plastic liners to form a complete plastic liner.

[0003] In actual plastic liner welding, the overall welding process is often accomplished using a tailstock assembly, positioning assembly, chuck assembly, correction mechanism, and heating mechanism. During operation, all welding components rest on two identical guide rails, ensuring extremely high coaxiality and linear motion. The machine operates smoothly, quickly, and efficiently. The chuck assembly positions the weld joint on both sides, the tailstock mechanism applies pressure on both sides, the correction mechanism locates and calibrates the weld end face, the positioning assembly positions the weld end, and the heating mechanism provides heat for welding.

[0004] However, during the production process, the welding process of plastic liners often deteriorates over time, and the resulting weld errors gradually increase, which in turn reduces the yield rate of the plastic liners produced. Furthermore, because the welds are melted and then solidified, there is a certain degree of uncontrollability. At the same time, accidental machine operation errors can also result in the production of defective products, thus affecting the overall yield rate of the plastic liners. Therefore, monitoring the welding process in plastic liners is very important. By using real-time monitoring of the welds, unqualified welded products can be quickly and accurately detected, or products with unqualified parameters can be eliminated, further ensuring the overall yield rate of the product and improving the production efficiency of good products. Summary of the Invention

[0005] The embodiments of the present application provide a process monitoring method, equipment and medium based on plastic liner welding, which are used to solve the following technical problems: In the existing plastic liner welding process, due to the actual deviation factors of the weld, it is easy to cause a certain error effect on the overall plastic liner after welding, thereby reducing the product qualification rate.

[0006] The embodiments of this application adopt the following technical solutions:

[0007] On the one hand, an embodiment of the present application provides a process monitoring method based on plastic liner welding, including: performing ultrasonic detection processing on the weld area of ​​the plastic liner to be inspected after welding under relevant phased radar to obtain ultrasonic data of the weld area; using a preset diffraction parallax method, performing defect assessment processing on the ultrasonic data of the weld area to obtain a weld ultrasonic assessment score of the weld area; if the weld ultrasonic assessment score is greater than a first standard score, performing image calculation processing on the weld area under relevant edge pixel slope to obtain the weld connection flatness of the weld area; and determining a weld flatness assessment score based on the weld connection flatness; if the weld flatness assessment score is greater than a second standard score, performing all-round monitoring of the overall configuration of the plastic liner through an infrared ray meter to obtain an overall configuration assessment score; determining a comprehensive assessment score of the plastic liner based on the weld ultrasonic assessment score, the weld flatness assessment score and the overall configuration assessment score; and classifying several plastic liners after inspection based on the comprehensive assessment score to obtain a set of plastic liner quality grades.

[0008] The embodiment of the present application can obtain ultrasonic data of the weld area more accurately through ultrasonic testing under phased radar, thereby improving the detection accuracy of weld defects. The preset diffraction parallax method is used to process the ultrasonic data to realize automatic defect assessment, reduce manual intervention, and improve assessment efficiency. By performing image calculation under the edge pixel slope of the weld area, the flatness of the weld connection can be evaluated, which is an indicator that is difficult to accurately measure using traditional methods. Combining the weld ultrasonic evaluation score, the weld flatness evaluation score and the overall configuration evaluation score, a comprehensive and integrated evaluation of the plastic liner can be performed to provide more comprehensive quality information. By setting standard scores, the plastic liner after inspection can be classified according to quality grades, which is helpful for quality control of the production process. Automated and standardized inspection processes can reduce inspection time and improve production efficiency. It reduces subjectivity and human errors in the manual inspection process and improves the consistency and reliability of inspection.

[0009] In one feasible embodiment, ultrasonic testing is performed on a weld area of ​​a plastic liner to be inspected after welding using a phased array radar to obtain ultrasonic data of the weld area. The method specifically includes: testing key parameters of a standard plastic liner weld area using phased array detection technology to obtain basic testing parameters, wherein the key parameters include at least a scanning mode, scanning coverage, probe-wedge matching, focusing parameters, and a fan scanning angle range; matching the basic testing parameters with an ultrasonic radar device for inspecting the plastic liner weld area to obtain a dedicated ultrasonic radar device; performing ultrasonic signal excitation processing on the weld area with full coverage using the dedicated ultrasonic radar device, and automatically controlling the gain of the excited ultrasonic signal within a pulse repetition frequency time period based on key technical indicators of the dedicated ultrasonic radar device to obtain an effective ultrasonic excitation signal, wherein the key technical indicators include the number of channels, sampling frequency, number of digitized bits, and time gain; recovering an ultrasonic reflection signal corresponding to the effective ultrasonic excitation signal; and converting the ultrasonic reflection signal into a digital signal to obtain ultrasonic data of the weld area based on the current plastic liner weld area.

[0010] In a feasible embodiment, the ultrasonic data of the weld area is subjected to defect assessment processing by a preset diffraction parallax method to obtain a weld ultrasonic assessment score of the weld area, specifically comprising: identifying the time delay data and the intensity change data in the ultrasonic data of the weld area; using a preset defect information template and based on the time delay data and the intensity change data, identifying the defect type of the weld area to obtain defect basic data; wherein the defect basic data includes: noise, position, deviation, depth, height, length and defect property type; using the diffraction parallax method and based on the time-amplitude waveform data between the time delay data and the intensity change data, the defect basic data is identified. Perform image generation processing under the diffraction effect to obtain a defect image; wherein the defect image is a cross-sectional image of the weld area; perform defect level evaluation on the defect image to obtain an unusable defect level and a usable defect level; wherein the unusable defect level is a defect level that has serious defects and cannot be used, and the usable defect level is a defect level that has minor defects and can be used; according to a preset expert evaluation system, perform decision evaluation on the defect parameters in the defect image at the usable defect level to obtain a weld ultrasonic evaluation score for the weld area; wherein the defect parameters include: defect size, defect location, defect type, defect nature, defect structural stress, and defect area size.

[0011] In a feasible embodiment, if the weld ultrasonic evaluation score is greater than the first standard score, the weld area is subjected to image calculation processing under the relevant edge pixel slope to obtain the weld connection flatness of the weld area, specifically including: if the weld ultrasonic evaluation score is greater than the first standard score, the weld area is subjected to image acquisition processing by an industrial camera under uniform rotation to obtain an initial weld area image; the initial weld area image is subjected to noise reduction and grayscale processing to obtain a weld area image; wherein the weld area is an extended image of the outer surface of the plastic liner; the edge contour pixel area perpendicular to the weld in the weld area image is identified; wherein the edge contour pixel area includes: weld area pixels, plastic liner area pixels on the left side of the weld, and plastic liner area pixels on the right side of the weld; the weld area pixels are compared with the plastic liner area pixels on the left side of the weld The pixels in the plastic liner area are collectively determined as pixels in the left weld connection area, and the pixels in the weld area and the pixels in the plastic liner area on the right side of the weld are collectively determined as pixels in the right weld connection area; according to the foreground and background separation technology, the background pixels of the left weld connection area pixels and the right weld connection area pixels are separated respectively to obtain left weld edge pixels and right weld edge pixels respectively; through the curve slope calculation algorithm, the slope of the edge pixels of the left weld edge pixels and the right weld edge pixels are calculated respectively to obtain left weld connection slope and right connection slope respectively; based on the left weld connection slope and the right weld connection slope, the left weld connection flatness and the right weld connection flatness are determined; wherein, the weld connection flatness includes: the left weld connection flatness and the right weld connection flatness.

[0012] In a feasible embodiment, based on the weld connection flatness, a weld flatness evaluation score is determined, specifically including: if the difference between the left weld connection flatness and the right weld connection flatness is greater than a first preset threshold, the current plastic liner is determined to be marked as a defective product; if the difference between the left weld connection flatness and the right weld connection flatness is less than or equal to the first preset threshold, the ratio between the left weld connection flatness and the right weld connection flatness is calculated to obtain the left and right side flatness ratio; according to a preset expert evaluation system and based on the left and right side flatness ratio, the plastic liner weld area is evaluated for weld flatness to obtain the weld flatness evaluation score.

[0013] In a feasible embodiment, if the weld flatness evaluation score is greater than the second standard score, the overall configuration of the plastic liner is monitored in all directions by means of an infrared ray meter to obtain an overall configuration evaluation score, specifically including: if the weld flatness evaluation score is greater than the second standard score, the outer surface length of the current plastic liner is laser measured by means of the infrared ray meter to obtain a length parameter; the outer surface width of the current plastic liner is laser measured to obtain a width parameter; and the outer surface height of the current plastic liner is laser measured to obtain a height parameter; wherein the length parameter, width parameter and height parameter are all static configuration parameters; the current plastic liner is rotated, and the current plastic liner in the rotating state is rotationally symmetrically measured to obtain dynamic configuration parameters; the dynamic configuration parameters are combined with the static configuration parameters to obtain overall configuration parameters; and the overall configuration parameters are evaluated under the overall configuration by a preset expert evaluation system to obtain the overall configuration evaluation score.

[0014] In a feasible embodiment, the comprehensive evaluation score of the plastic liner is determined based on the weld ultrasonic evaluation score, the weld flatness evaluation score and the overall configuration evaluation score, specifically including: dividing the weld ultrasonic evaluation score, the weld flatness evaluation score and the overall configuration evaluation score by proportional coefficients according to the proportion of plastic liner demand, and obtaining a first weight coefficient, a second weight coefficient and a third weight coefficient respectively; according to the first weight coefficient, the second weight coefficient and the third weight coefficient, performing a weighted calculation of the relevant evaluation scores on the weld ultrasonic evaluation score, the weld flatness evaluation score and the overall configuration evaluation score to obtain the comprehensive evaluation score of the current plastic liner.

[0015] In a feasible embodiment, the comprehensive evaluation scores are used to classify and process several plastic liners after inspection to obtain a set of plastic liners quality grades, specifically including: dividing the comprehensive evaluation scores into ranges according to a preset plastic liners quality grade range to determine the quality grade of each comprehensive evaluation score; and classifying and processing the corresponding plastic liners according to the quality grade of each comprehensive evaluation score to determine the plastic liners quality grade set.

[0016] In a second aspect, an embodiment of the present application also provides a process monitoring device based on plastic liner welding, the device comprising: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions that can be executed by the at least one processor, so that the at least one processor can execute a process monitoring method based on plastic liner welding as described in any of the above embodiments.

[0017] In a third aspect, an embodiment of the present application further provides a non-volatile computer storage medium, which is a non-volatile computer-readable storage medium. The non-volatile computer-readable storage medium stores at least one program, each of which includes instructions. When the instructions are executed by a terminal, the terminal executes a process monitoring method based on plastic liner welding as described in any of the above embodiments.

[0018] This application provides a process monitoring method, device, and medium based on plastic liner welding. Compared with the prior art, the embodiments of this application have the following beneficial technical effects:

[0019] 1. Improve detection accuracy: Through ultrasonic testing under phased array radar, ultrasonic data of the weld area can be obtained more accurately, thereby improving the detection accuracy of weld defects.

[0020] 2. Automated defect assessment: The preset diffraction parallax method is used to process ultrasonic data to achieve automated defect assessment, reducing manual intervention and improving assessment efficiency.

[0021] 3. Weld flatness assessment: By performing image calculation of the edge pixel slope of the weld area, the flatness of the weld connection can be evaluated, which is an indicator that is difficult to accurately measure using traditional methods.

[0022] 4. Comprehensive evaluation capability: Combining the weld ultrasonic evaluation score, weld flatness evaluation score, and overall configuration evaluation score, it can conduct a comprehensive evaluation of the plastic liner and provide more comprehensive quality information.

[0023] 5. Standardized quality grade classification: By setting standard scores, the tested plastic liners can be classified according to quality grades, which helps to control the quality of the production process.

[0024] 6. Improve production efficiency: Automated and standardized testing processes can reduce testing time and improve production efficiency.

[0025] 7. Reduce human errors: It reduces subjectivity and human errors in the manual inspection process and improves the consistency and reliability of inspection.

[0026] 8. Real-time monitoring and feedback: This method can monitor the quality of the welding process in real time and provide feedback when it reaches a certain standard, which helps to adjust the production process in a timely manner.

[0027] 9. Reduce costs: By improving inspection efficiency and reducing defect rates, product rework and repair costs can be reduced.

[0028] 10. Improve product reliability: By ensuring the welding quality of the plastic liner, the reliability and service life of the product are improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the following briefly introduces the drawings required for the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments described in the present application. For those skilled in the art, other drawings can be obtained based on these drawings without creative work. In the drawings:

[0030] Figure 1 A flow chart of a process monitoring method based on plastic liner welding provided in an embodiment of the present application;

[0031] Figure 2 A schematic diagram of welding error in the weld seam area of ​​a plastic liner provided in an embodiment of the present application;

[0032] Figure 3 A schematic structural diagram of a process monitoring device based on plastic liner welding provided in an embodiment of the present application. DETAILED DESCRIPTION

[0033] In order to enable those skilled in the art to better understand the technical solutions in this application, the following will clearly and completely describe the technical solutions in the embodiments of this application in conjunction with the drawings in the embodiments of this application. Obviously, the embodiments described are only part of the embodiments of this application, not all of the embodiments. Based on the embodiments of this specification, all other embodiments obtained by ordinary technicians in this field without making creative efforts should fall within the scope of protection of this application.

[0034] The embodiment of the present application provides a process monitoring method based on plastic liner welding, such as Figure 1 As shown, the process monitoring method based on plastic liner welding specifically includes steps S101-S106:

[0035] S101 , performing ultrasonic detection processing on the weld area of ​​the plastic liner to be inspected after welding under a phased control radar to obtain ultrasonic data of the weld area.

[0036] Specifically, phased array inspection technology is used to test key parameters of a standard plastic liner weld area to obtain basic inspection parameters. These key parameters include at least the scanning mode, scanning coverage, probe and wedge matching, focusing parameters, and sector scanning angle range.

[0037] Furthermore, the basic detection parameters are matched with the parameters of the ultrasonic radar equipment for detecting the weld area of ​​the plastic liner to obtain a dedicated ultrasonic radar equipment.

[0038] Furthermore, dedicated ultrasonic radar equipment is required to fully cover the weld area and perform ultrasonic signal excitation processing. Automatic gain control of the excited ultrasonic signal is performed within the pulse repetition frequency period based on the key technical indicators of the dedicated ultrasonic radar equipment to obtain an effective ultrasonic excitation signal. These key technical indicators include the number of channels, sampling frequency, number of digitized bits, and time gain.

[0039] Furthermore, the ultrasonic reflection signal corresponding to the effective ultrasonic excitation signal is recovered and then converted into a digital signal to obtain ultrasonic data of the weld area based on the current plastic liner weld area.

[0040] In one embodiment, during the process of using phased array detection equipment to detect the weld area of ​​a standard plastic liner, key parameters are tested, such as scanning mode (linear, circumferential, etc.), scanning coverage (weld width), probe and wedge matching (to ensure good coupling between the probe and the detection medium), focusing parameters (focusing depth and width), and fan scanning angle range (detection angle). The basic detection parameters obtained from the test are compared with the existing ultrasonic radar equipment. Based on the matching results, the ultrasonic radar equipment is customized or adjusted so that its parameters match the detection requirements of the standard plastic liner weld area. A dedicated ultrasonic radar device is used to excite ultrasonic signals that fully cover the weld area. Within the time period of the pulse repetition frequency, automatic gain control is performed according to key technical indicators (number of channels, sampling frequency, number of digitized bits, time gain) to ensure signal quality. The reflected signal after receiving the excited ultrasonic signal. The recovered ultrasonic reflection signal is digitized to obtain ultrasonic data of the weld area.

[0041] As a feasible implementation, optimizing focusing parameters and sector scanning angles improves detection depth and resolution, enabling clearer identification of weld defects. The application of technical indicators such as automatic gain control increases the automation of signal processing and reduces manual intervention. Combining phased array technology with specialized equipment enables more accurate identification of weld defects, reducing missed detections and false detections. Furthermore, customized ultrasonic radar equipment is more suitable for specific types of plastic liner weld inspection, improving the equipment's applicability and detection effectiveness.

[0042] S102. Perform defect assessment on the ultrasonic data of the weld area using a preset diffraction parallax method to obtain a weld ultrasonic assessment score for the weld area.

[0043] Specifically, time delay data and intensity variation data in ultrasonic data of the weld area are firstly identified.

[0044] Furthermore, using a preset defect information template, and based on the time delay data and intensity variation data, the weld area is identified for defect type, generating basic defect data. This basic defect data includes noise, location, deviation, depth, height, length, and defect type.

[0045] Furthermore, the diffraction parallax method is used to generate images based on the time-amplitude waveform data between the time delay data and the intensity change data. The defect basic data is processed under the diffraction effect to obtain a defect image. The defect image is a cross-sectional image of the weld area.

[0046] Furthermore, it is necessary to evaluate the defect level of the defect image to obtain an unusable defect level and a usable defect level. The unusable defect level is a defect level with serious defects and cannot be used, and the usable defect level is a defect level with minor defects and can be used.

[0047] Furthermore, a pre-set expert assessment system is used to make a decision and evaluate the defect parameters in the defect image at the applicable defect level to obtain the weld ultrasonic assessment score for the weld area. The defect parameters include defect size, defect location, defect type, defect nature, defect structural stress, and defect area size.

[0048] In a real-time example, Figure 2 A schematic diagram of welding error in the weld seam area of ​​a plastic liner provided in an embodiment of the present application is shown as follows: Figure 2 As shown, ultrasonic testing equipment is used to collect ultrasonic data from the weld area. Signal processing techniques are used to extract time delay data and intensity variation data from the ultrasonic data. Defect type identification is performed by designing or using existing defect information templates. The extracted time delay and intensity variation data are input into a defect recognition algorithm. The algorithm uses this data to identify the defect type and generate basic defect data, including noise, location, deviation, depth, height, length, and defect type. Simultaneously, the diffraction parallax method is applied to combine the time delay data with the intensity variation data to generate time-amplitude waveform data. This data is used to generate a defect image, a cross-sectional image of the weld area. The generated defect image can also be evaluated to determine the defect grade. This distinguishes between unusable defect grades (serious defects) and usable defect grades (minor defects). Furthermore, defect images with usable defect grades are analyzed using a pre-defined expert evaluation system. The system makes decisions and evaluations based on parameters such as defect size, location, type, nature, structural stress, and area size. An ultrasonic weld assessment score is generated for the weld area.

[0049] As a viable implementation, time delay and intensity variation data can accurately identify the defect type in the weld area. The defect image generated by the diffraction parallax method provides intuitive defect information, facilitating further analysis. Defect grade assessment can quickly distinguish the severity of the defect, helping to determine whether to continue using the component. Finally, the use of an expert assessment system improves the efficiency and accuracy of defect parameter assessment.

[0050] S103: If the weld ultrasonic evaluation score is greater than the first standard score, image calculation processing is performed on the weld area under the relevant edge pixel slope to obtain the weld connection flatness of the weld area. Based on the weld connection flatness, a weld flatness evaluation score is determined.

[0051] Specifically, if the weld ultrasonic assessment score is greater than the first standard score, an industrial camera is used to capture and process the weld area while it is rotating at a constant speed, generating an initial weld area image. This initial weld area image is subjected to noise reduction and grayscale processing to generate a weld area image. The weld area is an extended image of the outer surface of the plastic liner.

[0052] Furthermore, edge contour pixel regions perpendicular to the weld are identified in the weld region image, wherein the edge contour pixel regions include: weld region pixels, plastic liner region pixels to the left of the weld, and plastic liner region pixels to the right of the weld.

[0053] Furthermore, the weld area pixels and the plastic liner area pixels on the left side of the weld are collectively determined as the left weld connection area pixels, and the weld area pixels and the plastic liner area pixels on the right side of the weld are collectively determined as the right weld connection area pixels.

[0054] Furthermore, it is necessary to separate the background pixels of the left weld connection area pixels and the right weld connection area pixels according to the foreground and background separation technology to obtain the left weld edge pixels and the right weld edge pixels respectively.

[0055] Furthermore, the slope of the edge pixels of the left weld edge pixels and the right weld edge pixels are calculated respectively by using a curve slope calculation algorithm to obtain the left weld connection slope and the right weld connection slope respectively.

[0056] Furthermore, the left weld connection slope and the right weld connection slope are combined to determine the left weld connection flatness and the right weld connection flatness.

[0057] Furthermore, if the difference between the left and right weld seam flatness is greater than a first preset threshold, the plastic liner is determined to be defective and marked. If the difference between the left and right weld seam flatness is less than or equal to the first preset threshold, a ratio is calculated between the left and right weld seam flatness to obtain a left-right flatness ratio. Finally, the plastic liner weld area is evaluated for weld flatness based on the left-right flatness ratio using a preset expert evaluation system to obtain a weld flatness assessment score.

[0058] In one embodiment, Figure 2 As shown, image acquisition and processing are first performed: an industrial camera is used to capture images of the weld area while rotating at a constant speed. Denoising is then performed on the captured image to reduce image noise. The denoised image is then grayscale processed to simplify the image data. Next, edge contour pixel identification is performed: an image processing algorithm is used to identify edge contour pixels perpendicular to the weld in the weld area image. The weld area pixels, the plastic liner area pixels to the left of the weld, and the plastic liner area pixels to the right of the weld are determined. Next, the weld connection area pixels are determined: the weld area pixels are merged with the plastic liner area pixels to the left of the weld to determine the left weld connection area pixels. The weld area pixels are merged with the plastic liner area pixels to the right of the weld to determine the right weld connection area pixels. Background pixel separation is then performed: background pixels are separated from the left and right weld connection area pixels using foreground and background separation techniques. The left and right weld edge pixels are obtained. Curve slope calculation is also required: a curve slope calculation algorithm is applied to calculate the slopes of the left and right weld edge pixels. The left and right weld slopes are obtained. Next, the weld flatness is assessed: The left and right weld slopes are combined to determine the flatness of the welds. The flatness difference is checked to see if it exceeds a preset threshold to determine if the weld is defective. If the difference is less than or equal to the threshold, the left and right flatness ratio is calculated. Finally, an expert evaluation system is used: Using the preset expert evaluation system and the left and right flatness ratio, the weld area is evaluated for flatness. This generates a weld flatness assessment score.

[0059] As a feasible implementation method, noise reduction and grayscale processing can be used to improve image quality and facilitate subsequent processing. The weld area and the edge contours on both sides can then be accurately identified, facilitating subsequent analysis. By calculating the slope of the weld connection, the flatness of the weld connection can be evaluated. By comparing the difference in the flatness of the weld connections on both sides, potentially unqualified defective products can be quickly identified. The automated evaluation process reduces the need for manual inspection and improves production efficiency. It can also reduce the number of defective products and reduce the increased costs caused by defective products. Further ensuring the flatness of the weld connection improves the overall quality of the plastic liner.

[0060] S104. If the weld flatness assessment score is greater than the second standard score, the overall configuration of the plastic liner is comprehensively monitored using an infrared ray meter to obtain an overall configuration assessment score.

[0061] Specifically, if the weld flatness evaluation score is greater than the second standard score, the outer surface length of the current plastic liner is laser measured by an infrared ray meter to obtain the length parameter.

[0062] Furthermore, the width of the outer surface of the current plastic liner is measured by laser to obtain a width parameter. The height of the outer surface of the current plastic liner is also measured by laser to obtain a height parameter. The length parameter, width parameter, and height parameter are all static configuration parameters.

[0063] Furthermore, the current plastic liner is rotated, and rotational symmetry measurement is performed on the current plastic liner in the rotated state to obtain dynamic configuration parameters. The dynamic configuration parameters are combined with the static configuration parameters to obtain the overall configuration parameters.

[0064] Furthermore, the overall configuration parameters are evaluated under the overall configuration through a preset expert evaluation system to obtain an overall configuration evaluation score.

[0065] In one embodiment, a weld flatness assessment score is first calculated based on the previous weld flatness assessment process. The calculated weld flatness assessment score is compared with a preset second standard score. If the weld flatness assessment score is greater than the second standard score, a laser measurement of the outer surface of the plastic liner is performed using an infrared ray meter. The outer surface length of the plastic liner is measured using the infrared ray meter to obtain a length parameter. The outer surface width of the plastic liner is then measured to obtain a width parameter. Finally, the outer surface height of the plastic liner is measured to obtain a height parameter. The obtained length, width, and height parameters are then recorded; these parameters represent the static configuration of the plastic liner. The plastic liner is then rotated to a rotating state. The rotating plastic liner is then subjected to rotational symmetry measurement using an infrared ray meter to obtain dynamic configuration parameters. The static and dynamic configuration parameters are then combined to obtain the overall configuration parameters of the plastic liner. Finally, the overall configuration parameters are evaluated using a preset expert evaluation system. An overall configuration assessment score is generated based on the overall configuration parameters.

[0066] S105. Determine a comprehensive evaluation score of the plastic liner based on the weld ultrasonic evaluation score, the weld flatness evaluation score, and the overall configuration evaluation score.

[0067] Specifically, the weld ultrasonic evaluation score, weld flatness evaluation score and overall configuration evaluation score are divided into proportional coefficients according to the proportion of plastic liner demand, and the first weight coefficient, the second weight coefficient and the third weight coefficient are obtained respectively.

[0068] Furthermore, based on the first weight coefficient, the second weight coefficient and the third weight coefficient, the weld ultrasonic evaluation score, the weld flatness evaluation score and the overall configuration evaluation score are weightedly calculated to obtain the comprehensive evaluation score of the current plastic liner.

[0069] In one embodiment, weights are dynamically assigned based on product technical standards: 1. The quantitative basis (requirement percentage) for the weld ultrasonic assessment score can be pressure resistance (70 MPa → airtightness accounts for 60%), with a weight coefficient of α = 0.6; 2. The quantitative basis (requirement percentage) for the overall configuration assessment score can be cycle life (5000 cycles → structural strength accounts for 30%), with a weight coefficient of β = 0.3; 3. The quantitative basis (requirement percentage) for the weld flatness assessment score can be surface defect tolerance (appearance accounts for 10%), with a weight coefficient of γ = 0.1. The comprehensive assessment score is then calculated using the following model: S_{Comprehensive} = (S_{Ultrasonic}\times\alpha) + (S_{Configuration}\times\beta) + (S_{Smoothness}\times\gamma). For example: the ultrasonic inspection score S_Ultrasonic = 85 points (airtightness meets the standard); the configuration analysis score S_Configuration = 90 points (no stress concentration); and the flatness score S_Smooth = 70 points (minor scratches are present). The final calculation result is S_comprehensive = (85×0.6)+(90×0.3)+(70×0.1)=51+27+7=85 points, so the current comprehensive evaluation score of the plastic liner is judged to be qualified.

[0070] S106. Classify the tested plastic liners based on the comprehensive evaluation scores to obtain a set of plastic liners quality grades.

[0071] Specifically, the comprehensive evaluation scores are divided into ranges using a preset plastic liner quality grade range to determine the quality grade of each comprehensive evaluation score. Based on the quality grade of each comprehensive evaluation score, the corresponding plastic liners are classified and aggregated to determine a plastic liner quality grade set.

[0072] In addition, the embodiment of the present application also provides a process monitoring device based on plastic liner welding, such as Figure 3 As shown, the process monitoring equipment 300 based on plastic liner welding specifically includes:

[0073] At least one processor 301. And a memory 302 in communication with the at least one processor 301. The memory 302 stores instructions that can be executed by the at least one processor 301, so that the at least one processor 301 can execute:

[0074] The weld seam area of ​​the plastic liner to be inspected after welding is subjected to ultrasonic inspection under the relevant phased array radar to obtain ultrasonic data of the weld seam area.

[0075] The ultrasonic data of the weld area is processed for defect assessment using the preset diffraction parallax method to obtain the weld ultrasonic assessment score of the weld area.

[0076] If the weld ultrasonic evaluation score is greater than the first standard score, image calculation processing is performed on the weld area under the relevant edge pixel slope to obtain the weld connection flatness of the weld area; and based on the weld connection flatness, the weld flatness evaluation score is determined.

[0077] If the weld flatness assessment score is greater than the second standard score, the overall configuration of the plastic liner is monitored in all directions using an infrared ray meter to obtain an overall configuration assessment score.

[0078] The comprehensive evaluation score of the plastic liner is determined based on the weld ultrasonic evaluation score, weld flatness evaluation score and overall configuration evaluation score.

[0079] Through comprehensive evaluation scores, several plastic liners after testing are classified and processed to obtain a set of plastic liners quality grades.

[0080] The embodiment of the present application can obtain ultrasonic data of the weld area more accurately through ultrasonic testing under phased radar, thereby improving the detection accuracy of weld defects. The preset diffraction parallax method is used to process the ultrasonic data to realize automatic defect assessment, reduce manual intervention, and improve assessment efficiency. By performing image calculation under the edge pixel slope of the weld area, the flatness of the weld connection can be evaluated, which is an indicator that is difficult to accurately measure using traditional methods. Combining the weld ultrasonic evaluation score, the weld flatness evaluation score and the overall configuration evaluation score, a comprehensive and integrated evaluation of the plastic liner can be performed to provide more comprehensive quality information. By setting standard scores, the plastic liner after inspection can be classified according to quality grades, which is helpful for quality control of the production process. Automated and standardized inspection processes can reduce inspection time and improve production efficiency. It reduces subjectivity and human errors in the manual inspection process and improves the consistency and reliability of inspection.

[0081] The various embodiments in this application are described in a progressive manner. Similar portions between the various embodiments can be referred to in conjunction with each other. Each embodiment focuses on the differences between the other embodiments. In particular, the device and medium embodiments are generally similar to the method embodiments, so their descriptions are relatively simple. For relevant portions, refer to the descriptions of the method embodiments.

[0082] The devices and media provided in the embodiments of the present application correspond one-to-one to the methods. Therefore, the devices and media also have similar beneficial technical effects to their corresponding methods. Since the beneficial technical effects of the methods have been described in detail above, the beneficial technical effects of the devices and media will not be repeated here.

[0083] Those skilled in the art will appreciate that the embodiments of the present application can be provided as methods, systems, or computer program products. Therefore, the present application can adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the present application can adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) that contain computer-usable program code.

[0084] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 a process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0085] These computer program instructions may also be stored in a computer readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 a process or multiple processes and / or boxes Figure 1 The function specified in one or more boxes.

[0086] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing the instructions executed on the computer or other programmable device for implementing the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0087] In a typical configuration, a computing device includes one or more processors (CPUs), input / output interfaces, network interfaces, and memory.

[0088] Memory may include non-permanent storage in a computer-readable medium, random access memory (RAM) and / or non-volatile memory in the form of read-only memory (ROM) or flash RAM. Memory is an example of a computer-readable medium.

[0089] Computer-readable media includes permanent and non-permanent, removable and non-removable media that can be implemented by any method or technology to store information. The information can be computer-readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, compact disc read-only memory (CD-ROM), digital versatile disc (DVD) or other optical storage, magnetic cassettes, magnetic disk storage or other magnetic storage devices or any other non-transmission media that can be used to store information that can be accessed by a computing device. As defined herein, computer-readable media does not include transitory computer-readable media (transitory media), such as modulated data signals and carrier waves.

[0090] It should also be noted that the terms "comprises," "includes," or any other variations thereof are intended to encompass non-exclusive inclusion, such that a process, method, commodity, or apparatus that includes a series of elements includes not only those elements but also other elements not explicitly listed, or includes elements inherent to such process, method, commodity, or apparatus. In the absence of further limitations, an element defined by the phrase "comprises a ..." does not exclude the presence of other identical elements in the process, method, commodity, or apparatus that includes the element.

[0091] The foregoing is merely an embodiment of the present application and is not intended to limit the present application. For those skilled in the art, the present application may have various modifications and variations. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of the present application should all be included within the scope of the specification of the present application.

Claims

1. A process monitoring method based on plastic liner welding, characterized in that: The method comprises: Perform ultrasonic testing on the weld area of ​​the plastic liner to be inspected after welding under the relevant phased array radar to obtain ultrasonic data of the weld area; Performing defect assessment processing on the ultrasonic data of the weld area using a preset diffraction parallax method to obtain a weld ultrasonic assessment score for the weld area; If the weld ultrasonic evaluation score is greater than the first standard score, performing image calculation processing on the weld area under the relevant edge pixel slope to obtain the weld connection flatness of the weld area; and determining the weld flatness evaluation score based on the weld connection flatness; If the weld flatness evaluation score is greater than the second standard score, the overall configuration of the plastic liner is fully monitored using an infrared ray meter to obtain an overall configuration evaluation score; Determining a comprehensive evaluation score of the plastic liner based on the weld ultrasonic evaluation score, the weld flatness evaluation score, and the overall configuration evaluation score; The plurality of tested plastic liners are classified according to the comprehensive evaluation scores to obtain a set of plastic liner quality grades.

2. A process monitoring method based on plastic liner welding according to claim 1, characterized in that: The weld area of ​​the plastic liner to be inspected after welding is subjected to ultrasonic testing under phased array radar to obtain ultrasonic data of the weld area, including: Using phased array testing technology, key parameters of the standard plastic liner weld area are tested to obtain basic test parameters. These key parameters include at least: scanning mode, scanning coverage, probe and wedge matching, focusing parameters, and sector scanning angle range. Matching the basic detection parameters with the parameters of an ultrasonic radar device for detecting the weld area of ​​the plastic liner to obtain a dedicated ultrasonic radar device; The dedicated ultrasonic radar device is used to excite and process ultrasonic signals in full coverage of the weld area, and automatic gain control is performed on the excited ultrasonic signals within a pulse repetition frequency time period based on key technical indicators of the dedicated ultrasonic radar device to obtain an effective ultrasonic excitation signal; wherein the key technical indicators include: number of channels, sampling frequency, number of digitized bits, and time gain; Recovering an ultrasonic reflection signal corresponding to the effective ultrasonic excitation signal; The ultrasonic reflection signal is converted into a digital signal to obtain ultrasonic data of the weld area based on the current plastic liner weld area.

3. The process monitoring method based on plastic liner welding according to claim 1, characterized in that: The ultrasonic data of the weld area is subjected to defect assessment processing by a preset diffraction parallax method to obtain a weld ultrasonic assessment score of the weld area, specifically including: Identifying time delay data and intensity variation data in ultrasonic data of the weld region; Using a preset defect information template and based on the time delay data and the intensity change data, the defect type of the weld area is identified to obtain basic defect data; wherein the basic defect data includes: noise, position, deviation, depth, height, length, and defect property type; By using the diffraction parallax method and based on the time-amplitude waveform data between the time delay data and the intensity change data, the defect basic data is subjected to image generation processing under the relevant diffraction effect to obtain a defect image; wherein the defect image is a cross-sectional image of the weld area; Performing a defect level evaluation on the defect image to obtain an unusable defect level and a usable defect level; wherein the unusable defect level is a defect level in which a serious defect exists and the image cannot be used, and the usable defect level is a defect level in which a slight defect exists and the image can be used; According to a preset expert evaluation system, a decision evaluation is performed on the defect parameters in the defect image at the available defect level to obtain a weld ultrasonic evaluation score for the weld area; wherein the defect parameters include: defect size, defect location, defect type, defect nature, defect structural stress, and defect area size.

4. The process monitoring method based on plastic liner welding according to claim 1, characterized in that: If the weld ultrasonic evaluation score is greater than the first standard score, image calculation processing is performed on the weld area under the relevant edge pixel slope to obtain the weld connection flatness of the weld area, specifically including: If the weld ultrasonic evaluation score is greater than the first standard score, performing image acquisition and processing on the weld area rotating at a constant speed using an industrial camera to obtain an initial weld area image; Performing noise reduction and grayscale processing on the initial weld region image to obtain a weld region image; wherein the weld region is an extended image of the outer surface of the plastic liner; Identify edge contour pixel regions perpendicular to the weld in the weld region image; wherein the edge contour pixel regions include: weld region pixels, plastic liner region pixels to the left of the weld, and plastic liner region pixels to the right of the weld; The weld area pixels and the plastic liner area pixels on the left side of the weld are collectively determined as pixels in the left weld connection area, and the weld area pixels and the plastic liner area pixels on the right side of the weld are collectively determined as pixels in the right weld connection area; According to the foreground and background separation technology, the pixels in the left weld connection area and the pixels in the right weld connection area are respectively subjected to background pixel separation processing to obtain left weld edge pixels and right weld edge pixels respectively; The left weld edge pixels and the right weld edge pixels are respectively subjected to edge pixel slope calculation algorithm to obtain the left weld connection slope and the right weld connection slope respectively; Based on the left weld connection slope and the right weld connection slope, the left weld connection flatness and the right weld connection flatness are determined; wherein the weld connection flatness includes: the left weld connection flatness and the right weld connection flatness.

5. A process monitoring method based on plastic liner welding according to claim 4, characterized in that: Based on the weld flatness, a weld flatness evaluation score is determined, specifically including: If the difference between the left weld connection flatness and the right weld connection flatness is greater than a first preset threshold, the current plastic liner is determined to be defective and marked for processing; If the difference between the left weld connection flatness and the right weld connection flatness is less than or equal to the first preset threshold, a ratio of the left weld connection flatness to the right weld connection flatness is calculated to obtain a left-right flatness ratio; According to a preset expert evaluation system and based on the left and right side flatness ratio, the weld flatness of the plastic liner weld area is evaluated to obtain the weld flatness evaluation score.

6. The process monitoring method based on plastic liner welding according to claim 1, characterized in that: If the weld flatness evaluation score is greater than the second standard score, the overall configuration of the plastic liner is fully monitored using an infrared ray meter to obtain an overall configuration evaluation score, specifically including: If the weld flatness evaluation score is greater than the second standard score, the outer surface length of the current plastic liner is laser measured by the infrared ray meter to obtain a length parameter; Performing laser measurement on the width of the outer surface of the current plastic liner to obtain a width parameter; and performing laser measurement on the height of the outer surface of the current plastic liner to obtain a height parameter; wherein the length parameter, width parameter, and height parameter are all static configuration parameters; Rotating the current plastic liner, and performing rotational symmetry measurement on the current plastic liner in the rotating state to obtain dynamic configuration parameters; Combining the dynamic configuration parameters with the static configuration parameters to obtain overall configuration parameters; The overall configuration parameters are evaluated under the overall configuration by a preset expert evaluation system to obtain the overall configuration evaluation score.

7. The process monitoring method based on plastic liner welding according to claim 1, characterized in that: Based on the weld ultrasonic evaluation score, the weld flatness evaluation score, and the overall configuration evaluation score, a comprehensive evaluation score of the plastic liner is determined, specifically including: According to the proportion of plastic liner demand, the weld ultrasonic evaluation score, the weld flatness evaluation score, and the overall configuration evaluation score are divided by proportional coefficients to obtain a first weight coefficient, a second weight coefficient, and a third weight coefficient respectively; According to the first weight coefficient, the second weight coefficient and the third weight coefficient, the weld ultrasonic evaluation score, the weld flatness evaluation score and the overall configuration evaluation score are weightedly calculated to obtain the comprehensive evaluation score of the current plastic liner.

8. The process monitoring method based on plastic liner welding according to claim 1, characterized in that: The comprehensive evaluation scores are used to classify the tested plastic liners to obtain a set of plastic liners quality grades, specifically including: Divide the comprehensive evaluation scores into ranges according to the preset plastic liner quality grade ranges, and determine the quality grade of each comprehensive evaluation score; According to the quality level of each comprehensive evaluation score, the corresponding plastic liner is classified and aggregated to determine the plastic liner quality level set.

9. A process monitoring device based on plastic liner welding, characterized in that: The device comprises: at least one processor; and, a memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor, so that the at least one processor can execute the process monitoring method based on plastic liner welding according to any one of claims 1-8.

10. A non-volatile computer storage medium, characterized in that The storage medium is a non-volatile computer-readable storage medium, which stores at least one program. Each of the programs includes instructions. When the instructions are executed by the terminal, the terminal executes a process monitoring method based on plastic liner welding according to any one of claims 1 to 8.

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