Pipeline defect detection method and system

Abstract

The invention is suitable for the technical field of pipeline detection, and particularly relates to a pipeline defect detection method and system.The method comprises the steps that a pipeline defect detection area is delimited, a PID diagram of the detection area is drawn, a pipeline is segmented, a plurality of segments are obtained, defect data of each segment are collected through ultrasonic equipment, and the defect data of each segment are obtained; clustering the segments into defect segments, hidden danger segments and healthy segments; defining the hidden danger section as a deployment position of infrared thermal imaging equipment, marking an imaging range, collecting temperature distribution data of the hidden danger section, generating a temperature distribution diagram, querying a preset comparison table, and determining the number of groups. According to the method, the infrared imaging equipment is deployed in the hidden danger section, so that the hidden danger section can be monitored in real time, the defect can be quickly found, and the specific position of the defect can be further determined by determining the target group, so that accurate maintenance is facilitated, the maintenance cost is reduced, and the maintenance efficiency is greatly improved.

Description

Technical Field

[0001] The present invention relates to the technical field of pipeline detection, and particularly to a pipeline defect detection method and system. Background Art

[0002] In industries such as pipeline logistics, water supply, petrochemical, and natural gas, pipeline safety is of utmost importance, which requires pipeline defect detection. Pipeline defect detection refers to inspecting pipelines through various detection technologies (such as ultrasonic detection, X-ray detection, and artificial vision detection, etc.) to discover possible defects or damages and ensure the safe operation of pipelines. Common pipeline defects include corrosion, cracks, deformation, blockage, and sand holes, etc.

[0003] However, ultrasonic detection and X-ray detection cannot perform real-time monitoring and have high requirements for pipelines and scenarios. Artificial vision detection is prone to monitoring blind spots and cannot detect defects in a timely manner. Infrared thermal imaging equipment detects infrared radiation emitted from the pipeline surface to form a temperature distribution image and locates internal defects based on temperature changes. Therefore, "how to combine ultrasonic equipment and infrared thermal imaging equipment to perform real-time monitoring of pipelines" is the technical problem to be solved by the present invention. Summary of the Invention

[0004] The purpose of the present invention is to provide a pipeline defect detection method and system to solve the problem of "how to combine ultrasonic equipment and infrared thermal imaging equipment to perform real-time monitoring of pipelines" proposed in the above background art.

[0005] To achieve the above purpose, the present invention provides the following technical solutions: A pipeline defect detection method, the method comprising: Defining a detection area of pipeline defects, drawing a PID diagram of the detection area, dividing the pipeline to obtain several segments, using ultrasonic equipment to collect defect data of each segment, and clustering the segments into defect segments, potential hazard segments, and healthy segments; Defining the potential hazard segments as the deployment positions of infrared thermal imaging equipment, marking the imaging range, collecting temperature distribution data of the potential hazard segments, generating a temperature distribution diagram, querying a preset comparison table to determine the number of groups, and merging the pixels in the temperature distribution diagram according to the number of groups to obtain several pixel groups, wherein the comparison table consists of an imaging range item and a number of groups item; Calculating the temperature of each pixel group through the temperature distribution data and defining it as the group temperature, comparing the difference between the temperatures of two adjacent pixel groups, defining a target group based on the difference, and correcting the imaging range; Read out the transportation medium in the hidden danger section from the PID diagram, integrate the transportation medium and the target group, generate a detection report, and send the detection report to a preset terminal.

[0006] Further, the step of splitting the pipeline into several segments includes: Number each segment using a pre-established numbering rule; Configure the risk factors for each segment, where the risk factors at least include: historical data, transportation medium, and pipeline material, and determine the risk level.

[0007] Further, the step of using an ultrasonic device to collect defect data for each segment includes: Obtain the detection period of the ultrasonic device and establish a one-to-one correspondence between the detection period and the segment; Configure a set value. When the difference is greater than the set value, generate a detection request and push it to the preset terminal.

[0008] Further, the step of defining the hidden danger section as the deployment location of an infrared thermal imaging device, collecting the temperature distribution data of the hidden danger section, and generating a temperature distribution map includes: Use an ultrasonic device to collect the thermal image of the segment, calculate the temperature of each pixel to obtain the single-point temperature, and mark the single-point temperature on the PID diagram to generate a temperature distribution map; Add a color identifier to the temperature distribution map.

[0009] Further, the step of defining the hidden danger section as the deployment location of an infrared thermal imaging device, marking the imaging range, collecting the temperature distribution data of the hidden danger section, generating a temperature distribution map, querying a preset comparison table, and determining the number of groups includes: Judge whether the single-point temperatures corresponding to two adjacent pixels are the same. If so, merge them; Dynamically adjust the number of groups based on the risk level.

[0010] Further, the step of calculating the temperature of each pixel group through the temperature distribution data and defining it as the group temperature includes: Based on the numbering, identify the arrangement order of the pixel groups and establish a mapping between the pixel groups and unique identifiers; Use the unique identifier as the abscissa and the group temperature as the ordinate to draw a temperature change trend graph and integrate it into the detection report.

[0011] Further, the method further includes: Obtain a pre - formulated inspection route and use the hidden danger section to adjust the inspection route; Use an infrared thermal imaging device to construct a behavior monitoring mechanism, record the inspection time, integrate and generate an inspection schedule, and send the inspection schedule to a preset terminal.

[0012] Furthermore, the system includes: A clustering module, used to delimit the detection area of pipeline defects, draw the PID diagram of the detection area, divide the pipeline into several segments, use ultrasonic equipment to collect defect data of each segment, and cluster the segments into defect segments, hidden danger segments, and healthy segments; A obtaining module, used to define the hidden danger section as the deployment position of the infrared thermal imaging device, mark the imaging range, collect the temperature distribution data of the hidden danger section, generate a temperature distribution diagram, query a preset comparison table, determine the number of groups, and merge the pixels in the temperature distribution diagram according to the number of groups to obtain several pixel groups, where the comparison table consists of an imaging range item and a group number item; A correction module, used to calculate the temperature of each pixel group through the temperature distribution data, define it as the group temperature, compare the difference between the temperatures of two adjacent pixel groups, define a target group based on the difference, and correct the imaging range; A sending module, used to read the transportation medium in the hidden danger section from the PID diagram, integrate the transportation medium and the target group, generate a detection report, and send the detection report to a preset terminal.

[0013] Furthermore, the clustering module includes: A numbering unit, used to number each segment according to a pre - defined numbering rule; A determination unit, used to configure the risk factors of each segment, where the risk factors at least include: historical data, transportation medium, and pipeline material, and determine the risk level; A establishing unit, used to obtain the detection period of the ultrasonic equipment and establish a one - to - one correspondence between the detection period and the segment; A pushing unit, used to configure a set value, when the difference is greater than the set value, generate a detection request and push it to the preset terminal.

[0014] Furthermore, the obtaining module includes: A generating unit, used to use ultrasonic equipment to collect the thermal image of the segment, calculate the temperature of each pixel to obtain the single - point temperature, and mark the single - point temperature on the PID diagram to generate a temperature distribution diagram; An adding unit, used to add color marks to the temperature distribution diagram; A judgment unit, configured to judge whether the single-point temperatures corresponding to two adjacent pixels are the same. If so, merge them. An adjustment unit, configured to dynamically adjust the number of the groups based on the risk level.

[0015] Compared with the prior art, the beneficial effects of the present invention are as follows: By drawing a PID diagram, the topological structure between pipelines can be visually displayed, providing a data basis for pipeline defect detection. By dividing the pipeline into several segments, the position of the defect can be more accurately located, facilitating the hierarchical management of the pipeline. By using ultrasonic equipment, the pipeline can be nondestructively detected without affecting its normal use. By deploying an infrared imaging device in the hidden danger section, real-time monitoring of the hidden danger section can be achieved, and defects can be quickly discovered. By determining the target group, the specific position of the defect can be further confirmed for precise maintenance, reducing the maintenance cost and greatly improving the maintenance efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 It is a flowchart of the pipeline defect detection method provided by an embodiment of the present invention; Figure 2 It is a first sub-flowchart of the pipeline defect detection method provided by an embodiment of the present invention; Figure 3 It is a second sub-flowchart of the pipeline defect detection method provided by an embodiment of the present invention; Figure 4 It is a third sub-flowchart of the pipeline defect detection method provided by an embodiment of the present invention; Figure 5 It is a block diagram of the composition of the pipeline defect detection system provided by an embodiment of the present invention; Figure 6 It is a block diagram of the composition of the clustering module in the pipeline defect detection system provided by an embodiment of the present invention; Figure 7 It is a block diagram of the composition of the obtaining module in the pipeline defect detection system provided by an embodiment of the present invention; Figure 8 It is a block diagram of the composition of the correction module in the pipeline defect detection system provided by an embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0017] In order to make the objectives, technical solutions and advantages of the present invention clearer, the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention, but not to limit the present invention.

[0018] In Embodiment 1, Figure 1The implementation process of the pipeline defect detection method provided by the embodiments of the present invention is shown below, and the details are as follows: S100: Define the detection area of the pipeline defect, draw the PID diagram of the detection area, divide the pipeline to obtain several segments, use ultrasonic equipment to collect the defect data of each segment, and cluster the segments into defect segments, potential hazard segments, and healthy segments.

[0019] Determine the area that needs to be detected for pipeline defects, that is, the detection area. Collect equipment information such as equipment, pipelines, and valves, as well as material information from production managers or constructors. Combine with the existing pipeline layout diagram to draw the PID diagram; find the pipelines that need to be monitored in the PID diagram and divide them into several segments according to a preset step size, where the preset step size is formulated by the production manager.

[0020] Use ultrasonic equipment to perform ultrasonic detection on each segment. The ultrasonic equipment can be an ultrasonic flaw detector. Collect defect data such as the wall thickness, corrosion degree, and crack depth of the pipeline. According to the detection results, divide the pipeline into defect segments, potential hazard segments, and healthy segments. Among them, the defect segment refers to the segment with serious corrosion, deep cracks, or perforation. The defect segment needs to immediately repair or replace the pipeline. The potential hazard segment refers to the segment with slight wall thickness reduction, early corrosion, or surface cracks. The healthy segment refers to the segment without abnormalities and with good wall integrity.

[0021] S200: Define the deployment location of the infrared thermal imaging equipment as the potential hazard segment, mark the imaging range, collect the temperature distribution data of the potential hazard segment, generate a temperature distribution map, query the preset comparison table to determine the number of groups, and merge the pixels in the temperature distribution map according to the number of groups to obtain several pixel groups, where the comparison table consists of an imaging range item and a number of groups item.

[0022] Since the defect segment requires replacing the pipeline and the healthy segment has no abnormalities, neither of them needs real-time monitoring; therefore, deploy the infrared thermal imaging equipment at the potential hazard segment and use the infrared thermal imaging equipment to scan the pipeline at the potential hazard segment to determine the range of the scanning area, that is, the imaging range. The imaging range can be quantified by resolution, viewing angle, etc. Perform thermal imaging on the segments within the imaging range, collect the temperature distribution data of the potential hazard segment, and convert these data into a visual temperature distribution map; in real life, the areas with leakage or heat loss in the pipeline will have higher or lower temperatures and will show obvious temperature differences from adjacent areas. Through such characteristics, combined with the temperature distribution map, the specific defect location can be determined.

[0023] Using the quantized imaging range, query the look-up table to determine the number of groups, where the number of groups is 4×4 or 8×8, etc. The smaller the imaging range, the fewer the number of groups and the better the detection effect. The look-up table consists of the quantized value item of the imaging range and the number of groups item. Different imaging ranges correspond to different numbers of groups; according to the queried number of groups, merge the pixels in the temperature distribution map to obtain multiple pixel groups; the advantage of doing this is that it can initially determine the approximate area of the defect.

[0024] S300: Through the temperature distribution data, calculate the temperature of each pixel group and define it as the group temperature, compare the difference between the temperatures of two adjacent groups, based on the difference, define the target group, and correct the imaging range.

[0025] Using the calibration curve and temperature conversion formula of the infrared thermal imaging device, convert the acquired infrared radiation signal (radiance) into the actual temperature, calculate the temperature of each pixel group, that is, the group temperature; compare the difference between the temperatures of two adjacent groups. If the difference exceeds a certain set threshold, it indicates that there is a significant temperature change between these two adjacent pixel groups. Define these two adjacent pixel groups as the target group; based on the position and size of the target group, correct the original imaging range, further refine the number of pixels in each pixel group, and recalculate the group temperature of each pixel group; repeat the above steps until the target group corresponding to the smallest imaging range is found and determined as the final defect area.

[0026] For example, when the number of groups is 8×8, find three target groups A, B, and C, then refine the number of groups of each target group to 4×4, and recalculate the group temperature of the refined target group, and so on, until the target group with the smallest number of groups is found. This target group is the area where the pipeline defect is located.

[0027] S400: Read out the transport medium in the hidden danger section from the PID diagram, integrate the transport medium and the target group, generate a detection report, and send the detection report to a preset terminal.

[0028] Read out the transport medium in the hidden danger section, and write the location where the transport medium and the target group are located into a preset report template to generate a detection report, and send the detection report to a preset terminal, where the preset terminal is the production manager terminal.

[0029] In Embodiment 2, Figure 2 The implementation process of the pipeline defect detection method provided by the embodiment of the present invention is shown. The following details the steps of splitting the pipeline into several segments, as follows: S101: Number each of the segments using a pre-set numbering rule.

[0030] Number all the segments according to the numbering rules, where the numbering rules can be the specific characteristics of the pipeline, the order of the segments, and the geographical location. For example, the numbering rules can be "area number + segment serial number".

[0031] S102: Configure the risk factors for each of the segments, where the risk factors at least include: historical data, transportation medium, and pipeline material, and determine the risk level.

[0032] Determine the risk level for each segment according to the risk factors of each segment. For example, the risk level can be divided into high, medium, and low. For the location where a defect has occurred, the corresponding risk level should be high.

[0033] In Embodiment 3 Figure 2 The implementation process of the pipeline defect detection method provided by the embodiment of the present invention is shown. The following details the step of using an ultrasonic device to collect defect data for each segment, as follows: S103: Obtain the detection period of the ultrasonic device and establish a one-to-one correspondence between the detection period and the segment.

[0034] Set different detection periods for each segment. For example, a relatively frequent detection period can be set for the segments corresponding to the high risk level, and when the detection period arrives, use the ultrasonic device to detect pipeline defects.

[0035] S104: Configure a set value. When the difference is greater than the set value, generate a detection request and push it to the preset terminal.

[0036] In addition to detecting pipeline defects according to the detection period, when the difference between two adjacent pixel groups is greater than the set value, ultrasonic detection is also required; use the difference, the positions of the two adjacent pixel groups, the involved numbers, etc. to generate a detection request and send the detection request to the production manager terminal.

[0037] In this embodiment, if the difference between two adjacent pixel groups is greater than the set value, it indicates that there may be pipeline defects in the areas where these two pixel groups are located, and further detection is required.

[0038] In Embodiment 4 Figure 3 The implementation process of the pipeline defect detection method provided by the embodiment of the present invention is shown. The following details the step of defining the hidden danger segment as the deployment location of the infrared thermal imaging device, collecting the temperature distribution data of the hidden danger segment, and generating a temperature distribution map, as follows: S201: Use an ultrasonic device to collect the thermal images of the segmented sections, calculate the temperature of each pixel to obtain the single-point temperature, and mark the single-point temperature on the PID diagram to generate a temperature distribution diagram.

[0039] Use an ultrasonic device to scan each segmented section to obtain the thermal image of the pipe surface. The thermal image reflects the temperature information of each pixel. Through ultrasonic technology, identify the color or brightness intensity of each pixel, and use the temperature conversion formula to convert the thermal image into specific temperature values, denoted as the single-point temperature of each pixel. Mark the single-point temperature on the PID diagram to obtain the temperature distribution diagram. The advantage of constructing the temperature distribution diagram is that it can intuitively display the temperatures of different regions of the pipe.

[0040] S202: Add color markings to the temperature distribution diagram.

[0041] Divide the single-point temperature into several levels, each level corresponding to a color marking, and mark this color marking in the area corresponding to the level in the temperature distribution diagram.

[0042] In Embodiment 5, Figure 3 shows the implementation process of the pipeline defect detection method provided by the embodiment of the present invention. The following details the steps of defining the hidden danger section as the deployment position of the infrared thermal imaging device, marking the imaging range, collecting the temperature distribution data of the hidden danger section, generating the temperature distribution diagram, and querying the preset comparison table to determine the number of groups, as follows: S203: Determine whether the single-point temperatures corresponding to two adjacent pixels are the same. If so, merge them.

[0043] In the process of determining the pixel groups, if the single-point temperatures of two adjacent pixels are the same, directly merge these two pixels.

[0044] S204: Dynamically adjust the number of groups based on the risk level.

[0045] Adjust the number of groups according to the risk level. If the risk level of a certain segmented section is high, a smaller number of groups can be set. If the risk level is low, a larger number of groups can be set. The advantage of doing this is to strengthen the detection intensity of the pipeline with a higher risk level, so as to detect pipeline defects in a timely manner.

[0046] In Embodiment 6, Figure 4 shows the implementation process of the pipeline defect detection method provided by the embodiment of the present invention. The following details the steps of calculating the temperature of each pixel group from the temperature distribution data and defining it as the group temperature, as follows: S301: Based on the said numbering, identify the arrangement order of the pixel groups, and establish a mapping between the pixel groups and unique identifiers.

[0047] According to the numbering of each segment, determine the unique identifier of each pixel group, and establish a mapping relationship between the pixel group and the unique identifier; wherein the unique identifier should be formulated according to the arrangement order.

[0048] S302: Using the unique identifier as the abscissa and the group temperature as the ordinate, draw a temperature change trend graph and integrate it into the detection report.

[0049] Using the unique identifier as the abscissa and the group temperature as the ordinate, draw a temperature change trend graph; the advantage of doing this is that it can more intuitively display the temperature change of the pipeline; integrate the temperature change trend graph into the detection report, so as to provide decision-making support for production managers.

[0050] In Embodiment 7, different from Embodiment 1, in the embodiment of the present invention, the method further includes: Obtain a pre-determined inspection route, and use the hidden danger segment to adjust the inspection route; Using an infrared thermal imaging device, construct a behavior monitoring mechanism, record the inspection time, integrate and generate an inspection schedule, and send the inspection schedule to a preset terminal.

[0051] During the daily production process, production managers will formulate an inspection route according to the layout of pipelines or equipment, historical inspection data and preset inspection plans; after determining the hidden danger segment, add the location of the hidden danger segment to the inspection route to realize the combination of manual inspection and infrared thermal imaging device inspection.

[0052] Through the infrared thermal imaging device, combined with the behavior monitoring mechanism, record the inspection time, integrate all the inspection times, generate an inspection schedule, and send the inspection schedule to a preset terminal, wherein the behavior monitoring mechanism is: when the infrared thermal imaging device monitors that the human body information is within the segment and circles around the segment as the center, it means that the staff has inspected this segment.

[0053] Figure 5 The composition structure block diagram of the pipeline defect detection system provided by the embodiment of the present invention is shown. The pipeline defect detection system 1 includes: The clustering module 11 is used to delimit the detection area of the pipeline defect, draw the PID diagram of the detection area, cut the pipeline to obtain several segments, use ultrasonic equipment to collect the defect data of each segment, and cluster the segments into defect segments, hidden danger segments and healthy segments; The obtaining module 12 is configured to define the hidden danger section as the deployment location of the infrared thermal imaging device, mark the imaging range, collect the temperature distribution data of the hidden danger section, generate a temperature distribution map, query a preset comparison table, determine the number of groups, and merge the pixels in the temperature distribution map according to the number of groups to obtain a plurality of pixel groups, where the comparison table consists of an imaging range item and a group number item; The correction module 13 is configured to calculate the temperature of each pixel group via the temperature distribution data, define it as the group temperature, compare the difference between the temperatures of two adjacent groups, define a target group based on the difference, and correct the imaging range; The sending module 14 is configured to read the transport medium in the hidden danger section from the PID diagram, integrate the transport medium and the hidden danger section, generate a detection report, and send the detection report to a preset terminal.

[0054] Figure 6 The block diagram showing the composition structure of the pipeline defect detection system provided by an embodiment of the present invention, the clustering module 11 includes: The numbering unit 111 is configured to number each of the segments using a pre - defined numbering rule; The determining unit 112 is configured to configure the risk factors for each of the segments, where the risk factors at least include: historical data, transport medium, and pipeline material, and determine the risk level; The establishing unit 113 is configured to obtain the detection period of the ultrasonic device and establish a one - to - one correspondence between the detection period and the segment; The pushing unit 114 is configured to configure a set value, and when the difference is greater than the set value, generate a detection request and push it to the preset terminal.

[0055] Figure 7 The block diagram showing the composition structure of the pipeline defect detection system provided by an embodiment of the present invention, the obtaining module 12 includes: The generating unit 121 is configured to use an ultrasonic device to collect a thermal image of the segment, calculate the temperature of each pixel to obtain a single - point temperature, mark the single - point temperature on the PID diagram, and generate a temperature distribution map; The adding unit 122 is configured to add a color identifier to the temperature distribution map; The judging unit 123 is configured to judge whether the single - point temperatures corresponding to two adjacent pixels are the same, and if so, merge them; The adjusting unit 124 is configured to dynamically adjust the number of groups based on the risk level.

[0056] Figure 8The block diagram of the composition of the pipeline defect detection system provided by the embodiment of the present invention is shown. The correction module 13 includes: A mapping unit 131, configured to identify the arrangement order of the pixel groups according to the number, and establish a mapping between the pixel groups and unique identifiers; An integration unit 132, configured to draw a temperature change trend graph with the unique identifier as the abscissa and the group temperature as the ordinate, and integrate it into the detection report.

[0057] Among them, the clustering module 11 is mainly used to complete step S100, the module 12 is mainly used to complete step S200, the correction module 13 is mainly used to complete step S300, and the sending module 14 is mainly used to complete step S400; The numbering unit 111 is mainly used to complete step S101, the determination unit 112 is mainly used to complete step S102, the establishment unit 113 is mainly used to complete step S103, and the pushing unit 114 is mainly used to complete step S104; The generating unit 121 is mainly used to complete step S201, the adding unit 122 is mainly used to complete step S202, the judging unit 123 is mainly used to complete step S203, and the adjusting unit 124 is mainly used to complete step S204; The mapping unit 131 is mainly used to complete step S301, and the integration unit 132 is mainly used to complete step S302.

[0058] The technical features of the above embodiments can be combined arbitrarily. For the sake of concise description, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, it should be considered as the scope described in this specification.

[0059] The above embodiments only represent several implementation manners of the present invention. The description is relatively specific and detailed, but it should not be construed as a limitation on the scope of the patent of the present invention. It should be noted that for those of ordinary skill in the art, without departing from the concept of the present invention, several deformations and improvements can still be made, and these all belong to the protection scope of the present invention. Therefore, the protection scope of the patent of the present invention should be subject to the appended claims.

[0060] The above is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent replacements, and improvements made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A pipeline defect detection method, characterized in that: The method comprises: Delineate the detection area of ​​pipeline defects, draw a PID diagram of the detection area, divide the pipeline into several segments, collect defect data of each segment using ultrasonic equipment, and cluster the segments into defective segments, potential danger segments, and healthy segments; The hidden danger section is defined as the deployment position of the infrared thermal imaging device, and the imaging range is marked, the temperature distribution data of the hidden danger section is collected, a temperature distribution map is generated, a preset comparison table is queried, the number of groups is determined, and the pixels in the temperature distribution map are merged according to the number of groups to obtain a plurality of pixel groups, wherein the comparison table is composed of an imaging range item and a group number item; Calculate the temperature of each pixel group through the temperature distribution data and define it as the group temperature, compare the difference between the temperatures of two adjacent groups, define the target group based on the difference, and correct the imaging range; From the PID map, the transport medium in the potential danger section is read out, the transport medium and the target group are integrated, a detection report is generated, and the detection report is sent to a preset terminal.

2. The pipeline defect detection method according to claim 1, characterized in that: The step of dividing the pipeline into a plurality of segments comprises: Numbering each of the segments using a predetermined numbering rule; The risk factors for each of the segments are configured, wherein the risk factors at least include: historical data, transport medium and pipeline material, and the risk level is determined.

3. The pipeline defect detection method according to claim 1, characterized in that: The step of collecting defect data of each segment by using ultrasonic equipment includes: Obtaining a detection cycle of an ultrasonic device, and establishing a one-to-one correspondence between the detection cycle and the segments; A set value is configured, and when the difference is greater than the set value, a detection request is generated and pushed to the preset terminal.

4. The pipeline defect detection method according to claim 2, characterized in that: The step of defining the potential danger section as the deployment position of the infrared thermal imaging device, collecting the temperature distribution data of the potential danger section, and generating a temperature distribution map comprises: Using ultrasonic equipment, collecting the segmented thermal images, calculating the temperature of each pixel, obtaining a single-point temperature, and marking the single-point temperature in a PID map to generate a temperature distribution map; Add a color identifier to the temperature distribution map.

5. The pipeline defect detection method according to claim 4, characterized in that: The steps of defining the potential danger section as the deployment location of the infrared thermal imaging device, marking the imaging range, collecting the temperature distribution data of the potential danger section, generating a temperature distribution map, querying a preset comparison table, and determining the number of groups include: Determine whether the single point temperatures corresponding to two adjacent pixels are the same, and if so, merge them; Based on the risk level, the number of groups is dynamically adjusted.

6. The pipeline defect detection method according to claim 2, characterized in that: The step of calculating the temperature of each pixel group based on the temperature distribution data and defining the temperature as the group temperature comprises: Based on the serial numbers, identifying the arrangement order of the pixel groups, and establishing a mapping between the pixel groups and unique identifiers; With the unique identifier as the horizontal axis and the group temperature as the vertical axis, a temperature change trend graph is drawn and integrated into the detection report.

7. The pipeline defect detection method according to claim 1, characterized in that: The method further comprises: Obtaining a pre-determined inspection route, and adjusting the inspection route using the hidden danger section; Using infrared thermal imaging equipment, a behavior monitoring mechanism is constructed to record the inspection time, integrate and generate an inspection schedule, and send the inspection schedule to a preset terminal.

8. A pipeline defect detection system, characterized in that: The system comprises: The clustering module is used to define the detection area of ​​pipeline defects, draw the PID diagram of the detection area, divide the pipeline into several segments, collect the defect data of each segment by ultrasonic equipment, and cluster the segments into defective segments, hidden danger segments and healthy segments; A module is provided for defining the potential danger section as the deployment position of the infrared thermal imaging device, marking the imaging range, collecting the temperature distribution data of the potential danger section, generating a temperature distribution map, querying a preset comparison table, determining the number of groups, and merging the pixels in the temperature distribution map according to the number of groups to obtain a plurality of pixel groups, wherein the comparison table is composed of an imaging range item and a group number item; A correction module, used to calculate the temperature of each pixel group through the temperature distribution data and define it as the group temperature, compare the difference between the temperatures of two adjacent groups, define a target group based on the difference, and correct the imaging range; The sending module is used to read the transport medium in the potential danger section from the PID map, integrate the transport medium and the target group, generate a detection report, and send the detection report to a preset terminal.

9. The pipeline defect detection system according to claim 8, characterized in that: The clustering module comprises: A numbering unit, used to number each of the segments using a predetermined numbering rule; A determination unit, configured to configure risk factors for each of the segments, wherein the risk factors at least include: historical data, transport medium and pipeline material, and determine the risk level; An establishing unit, used for acquiring a detection period of an ultrasonic device and establishing a one-to-one correspondence between the detection period and the segment; The push unit is used to configure a set value, and when the difference is greater than the set value, generate a detection request and push it to the preset terminal.

10. The pipeline defect detection system according to claim 9, characterized in that: The obtaining module comprises: A generating unit, used to collect the segmented thermal images by using an ultrasonic device, calculate the temperature of each pixel, obtain a single-point temperature, and mark the single-point temperature in a PID map to generate a temperature distribution map; An adding unit, used for adding a color mark to the temperature distribution map; A judging unit, used to judge whether the single point temperatures corresponding to two adjacent pixels are the same, and if so, merge them; An adjustment unit is used to dynamically adjust the number of groups based on the risk level.

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