A pipeline defect detection system and method based on transmission type terahertz spectrum

Abstract

The application discloses a pipeline defect detection system and method based on transmission type terahertz spectrum, which comprises a fixed seat and a movable ring located on the fixed seat; the movable ring can rotate relative to the fixed seat; along the circumference of the movable ring, three groups of terahertz detection components are distributed at equal intervals; a polyethylene gas pipe is conveyed to a terahertz signal radiation area along a conveying belt; the terahertz signal radiation area is an in-ring sampling area of the movable ring; the movable ring rotates back and forth in the circumferential direction; after a terahertz signal penetrates the polyethylene gas pipe and carries information of the wall thickness and defects of the gas pipe is collected by a terahertz detector and imaged, the information is transmitted to a computer image data processing and analysis, a three-dimensional model of the polyethylene gas pipe is established, potential defects are visually displayed and marked. Compared with the prior art, the polyethylene gas pipe defect online detection system can realize omnibearing size monitoring and internal defect monitoring, and has the characteristics of high detection efficiency, high speed and high accuracy.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of non-destructive testing equipment production, and in particular to a pipeline defect detection system and method based on transmission type terahertz spectroscopy. BACKGROUND

[0002] Polyethylene material is the first choice of pipeline material in the field of gas pipeline due to its light weight, long service life, strong corrosion resistance, stable performance and other characteristics. Since the gas pipe is usually buried, once the pipeline is damaged, fails or leaks, it will cause a major safety accident. Therefore, the product quality of polyethylene gas pipe is an important prerequisite to ensure its safe use. However, there is still a lack of real-time, fast and accurate detection device for defects generated during the production process of polyethylene gas pipe.

[0003] During the processing of the pipeline, various defects may occur, such as porosity problems, uneven wall thickness problems, roundness problems and pipe wall sagging problems.

[0004] In existing industrial production, enterprises use ultrasonic thickness measurement devices to detect polyethylene gas pipes. Although the ultrasonic detection device can measure the wall thickness with a certain accuracy, it at least has the following disadvantages:

[0005] 1. The existing ultrasonic measurement device cannot detect the tiny defects inside the pipeline due to the resolution limit. The cavities inside the pipeline that cannot be detected by ultrasonic waves may affect the quality of the pipeline.

[0006] 2. Ultrasonic measurement technology is a contact measurement method, which may affect the outer wall of the pipe. In order to improve the measurement accuracy, a coupling agent needs to be applied, which may contaminate the pipeline and increase the uncertainty in the measurement process. SUMMARY

[0007] The present application aims to overcome the shortcomings and deficiencies of the prior art and provide a real-time, fast and accurate pipeline defect detection system and method based on transmission type terahertz spectroscopy.

[0008] The present application is achieved by the following technical solutions:

[0009] A pipeline defect detection system based on transmission type terahertz spectroscopy, comprising a fixed seat 2 and a dynamic ring 1 located on the fixed seat 2; the dynamic ring 1 can rotate relative to the fixed seat 2;

[0010] Along the circumference of the dynamic ring 1, there are three groups of terahertz detection components equally distributed;

[0011] Each group of terahertz detection components includes a terahertz source 3 and a terahertz detector 4;

[0012] The terahertz source 3 and the terahertz detector 4 in each group are arranged on the corresponding side of the circumference and on the same diameter line.

[0013] The terahertz signal emitted by the terahertz source 3 in each group passes through the sampling area in the ring of the dynamic ring 1 and reaches the terahertz detector 4 on the corresponding side.

[0014] The dynamic ring 1 can rotate relative to the fixed seat 2 at an angle of 0-180°.

[0015] The terahertz detector 4 of each terahertz detection assembly is signal-connected with the computer 5.

[0016] A pipeline defect detection method comprises the following steps:

[0017] The polyethylene gas pipe is conveyed to the terahertz signal radiation area by a conveyor belt; the terahertz signal radiation area is the sampling area in the ring of the dynamic ring 1; the dynamic ring 1 rotates circumferentially and reciprocally;

[0018] The terahertz signal penetrates the polyethylene gas pipe, the terahertz signal carrying information of the wall thickness and defects of the gas pipe is collected by the terahertz detector 4 and imaged, and then transmitted to the computer 5 for image data processing and analysis, so as to establish a three-dimensional model of the polyethylene gas pipe, visually display and mark potential defects.

[0019] The image data processing and analysis process is as follows:

[0020] ①The computer 5 obtains the conveying speed of the polyethylene gas pipe and the circumferential rotation speed of the dynamic ring 1;

[0021] ②Three terahertz detection assemblies constitute channel one, channel two and channel three; the computer 5 simultaneously calculates the spatial orientation of the scanning area of channel one, the spatial orientation of the scanning area of channel two and the spatial orientation of the scanning area of channel three at the current time, and simultaneously obtains the spectral data of the scanning area of channel one, the spectral data of the scanning area of channel two and the spectral data of the scanning area of channel three at the current time;

[0022] ③The spatial coordinate relationship of each discrete spectral data point of each channel is calculated to form a spectral-coordinate data point set of each channel;

[0023] ④The spectral-coordinate data point sets of the channels are integrated to form a total pipeline spectral-coordinate data point set;

[0024] ⑤A potential defect area discrimination algorithm is used to discriminate the potential defects of each coordinate in the total spectral-coordinate data point set to form a defect-coordinate data point set;

[0025] ⑥A polyethylene gas pipeline quality cloud chart drawing algorithm is used to draw a polyethylene pipeline quality cloud chart;

[0026] The potential defect area judgment algorithm flow is:

[0027] ①Reading the terahertz detector 4 signal of each channel, and inputting it into the program as a pipeline spectrum-coordinate data point set;

[0028] ②Analyzing the pipeline spectrum data of each channel, and using the time domain signal to determine whether there is a defect in the pipeline;

[0029] ③Time-frequency conversion is performed on the time domain spectrum data, and each frequency domain spectrum is input into the defect classification model for judgment.

[0030] ④Comprehensive time-frequency domain judgment result, build defect-coordinate data point set.

[0031] The time-frequency conversion is a fast Fourier transform algorithm.

[0032] The polyethylene gas pipeline quality cloud drawing algorithm is:

[0033] ①Input the polyethylene pipeline defect-coordinate data point set at the current time;

[0034] ②Draw the defect scatter plot of the overall polyethylene pipeline at the current time;

[0035] ③Draw the polyethylene pipeline quality cloud map at the current time using the bicubic interpolation algorithm;

[0036] ④Draw the overall polyethylene pipeline quality cloud map combined with historical cloud map data.

[0037] During the detection process, the conveying speed of the polyethylene pipeline needs to be matched with the rotating speed of the dynamic ring 1 as the detection, and the speed relationship is as follows:

[0038]

[0039] Wherein: the polyethylene pipeline conveying speed is Vtube, the dynamic ring 1 rotating angular velocity is ωloop, the terahertz detector 4 receiving range length is L, the diameter of the circle where the terahertz detector 4 and the terahertz source 3 are located is D, and the polyethylene pipeline diameter is d.

[0040] Compared with the prior art, the present application has the following advantages and effects:

[0041] The present application has three groups of terahertz detection components equidistantly distributed along the circumference of the ring 1; each group of terahertz detection components includes a terahertz source 3 and a terahertz detector 4; during operation, the polyethylene gas pipe is conveyed to the terahertz signal radiation area along with the conveying belt; the terahertz signal radiation area is the sampling area in the ring 1; the ring 1 rotates back and forth in the circumferential direction; the terahertz signal penetrates the polyethylene gas pipe, carries the information of the gas pipe wall thickness and defects, is collected by the terahertz detector 4 and imaged, and then is transmitted to the computer 5 for image data processing and analysis, to establish a three-dimensional model of the polyethylene gas pipe, visually display and mark potential defects. The present application adopts the above scheme, can detect the defects inside the polyethylene gas pipe, has high detection efficiency, and can also realize online ring scanning of the pipe and defect cloud chart drawing modeling; the present application can perform full detection on all areas of the polyethylene gas pipe, there is no area missed in detection, and the accuracy of the detection result is ensured. BRIEF DESCRIPTION OF DRAWINGS

[0042] Figure 1 is a detection module structure diagram of the polyethylene gas pipe defect online detection system based on the transmission type terahertz spectrum of the present application;

[0043] Figure 2 is a data processing flow chart of the image data processing and analysis matched with the polyethylene gas pipe defect online detection system based on the transmission type terahertz spectrum of the present application;

[0044] Figure 3 is a potential defect area discrimination algorithm flow chart matched with the polyethylene gas pipe defect online detection system based on the transmission type terahertz spectrum of the present application;

[0045] Figure 4 is a pipe quality cloud chart drawing algorithm flow chart matched with the polyethylene gas pipe defect online detection system based on the transmission type terahertz spectrum of the present application. DETAILED DESCRIPTION

[0046] The present application will be further specifically and in detail described below in combination with specific embodiments.

[0047] As shown in Figures 1-4 The present application discloses a pipeline defect detection system based on the transmission type terahertz spectrum, characterized in that it includes a fixed seat 2 and a ring 1 located on the fixed seat 2; the ring 1 can rotate relative to the fixed seat 2;

[0048] Three groups of terahertz detection components are equidistantly distributed along the circumference of the ring 1; in actual application, two groups or more than three groups can be used, and the specific number is subject to actual application.

[0049] Each group of terahertz detection components includes a terahertz source 3 and a terahertz detector 4;

[0050] The terahertz source 3 and the terahertz detector 4 in each group are arranged on the corresponding side of the circumference and on the same diameter line.

[0051] The terahertz signal emitted by the terahertz source 3 in each group passes through the sampling area in the ring of the dynamic ring 1 and reaches the terahertz detector 4 on the corresponding side.

[0052] The terahertz detector 4 of each terahertz detection assembly is signal-connected with the computer 5.

[0053] The terahertz source 3 is preferably a 600 GHz terahertz source.

[0054] The terahertz detector 4 is preferably a high-speed terahertz linear detector.

[0055] The dynamic ring 1 can rotate relative to the fixed seat 2 at an angle of 0-180°. The rotating action of the dynamic ring 1 can adopt a conventional driving mode such as a servo motor driving mode or a manual driving mode.

[0056] A pipeline defect detection method can be implemented by the following steps:

[0057] The polyethylene gas pipe is conveyed to the terahertz signal radiation area by a conveyor belt; the terahertz signal radiation area is the sampling area in the ring of the dynamic ring 1; and the dynamic ring 1 rotates circumferentially and reciprocally.

[0058] The terahertz signal penetrates the polyethylene gas pipe, carries the information of the wall thickness and defects of the gas pipe, is collected by the terahertz detector 4, and is imaged and then transmitted to the computer 5 for image data processing and analysis, so as to establish a three-dimensional model of the polyethylene gas pipe, visually display and mark potential defects.

[0059] The image data processing and analysis process is as follows:

[0060] ① The computer 5 obtains the conveying speed of the polyethylene gas pipe and the circumferential rotation speed of the dynamic ring 1;

[0061] ② The three terahertz detection assemblies constitute channel one, channel two and channel three; the computer 5 simultaneously calculates the spatial orientation of the scanning area of channel one, the spatial orientation of the scanning area of channel two and the spatial orientation of the scanning area of channel three at the current time, and simultaneously obtains the spectral data of the scanning area of channel one, the spectral data of the scanning area of channel two and the spectral data of the scanning area of channel three at the current time;

[0062] ③ The spatial coordinate relationship of each discrete spectral data point of each channel is calculated to form a spectral-coordinate data point set of each channel;

[0063] ④ The spectral-coordinate data point sets of the channels are integrated to construct a total pipeline spectral-coordinate data point set;

[0064] 5. The potential defect area discrimination algorithm is used to discriminate the potential defects of each coordinate in the overall spectral-coordinate data point set, and a defect-coordinate data point set is constructed;

[0065] 6. The polyethylene gas pipeline quality cloud map drawing algorithm is used to draw the polyethylene pipeline quality cloud map;

[0066] The potential defect area discrimination algorithm process is as follows:

[0067] 1. The terahertz detector 4 signals of each channel are read and input into the program as the pipeline spectral-coordinate data point set;

[0068] 2. The pipeline spectral data of each channel is analyzed, and the time domain signal is used to determine whether there is a defect inside the pipeline;

[0069] 3. The time-frequency conversion is performed on the time domain spectral data, and each frequency domain spectrum is input into the defect classification model for judgment. If it is judged to be true, it is considered that the region where the discrete data point is located contains a defect, and the defect depth regression model is used to calculate the defect depth. If it is judged to be false, it is considered that the region where the discrete data point is located does not contain a defect;

[0070] 4. The discrimination results in the time and frequency domains are integrated to construct a defect-coordinate data point set.

[0071] The time-frequency conversion is a fast Fourier transform algorithm.

[0072] The polyethylene gas pipeline quality cloud map drawing algorithm is as follows:

[0073] 1. The current time polyethylene pipeline defect-coordinate data point set is input;

[0074] 2. The current time defect scatter plot of the overall region of the polyethylene pipeline is drawn;

[0075] 3. The current time polyethylene pipeline quality cloud map is drawn using the bicubic interpolation algorithm;

[0076] 4. The overall polyethylene pipeline quality cloud map is drawn in combination with the historical cloud map data.

[0077] During the detection process, the polyethylene pipeline conveying speed needs to be matched with the rotating speed of the moving ring 1 as the detection, and the speed relationship is as follows:

[0078]

[0079] Wherein: the polyethylene pipeline conveying speed is V tube , the rotating angular velocity of the moving ring 1 is ω loop , the receiving range length of the terahertz detector 4 is L, the diameter of the circle where the terahertz detector 4 and the terahertz source 3 are located is D, and the diameter of the polyethylene pipeline is d.

[0080] As described above, the present application can be well implemented.

[0081] The embodiments of the present application are not limited to the above examples, and any changes, modifications, substitutions, combinations, simplifications made without departing from the spirit and principles of the present application shall be equivalent replacements and shall be included in the protection scope of the present application.

Claims

1. A method of pipe defect detection, characterized by The pipeline defect detection system based on transmission type terahertz spectrum is realized; the pipeline defect detection system comprises a fixed seat (2) and a movable ring (1) located on the fixed seat (2); the movable ring (1) can rotate relative to the fixed seat (2); Along the circumference of the movable ring (1), three groups of terahertz detection components are equidistantly distributed; Each group of terahertz detection components comprises a terahertz source (3) and a terahertz detector (4); The terahertz source (3) and the terahertz detector (4) in each group are respectively arranged on the corresponding side of the circumference and on the same diameter line; The terahertz signal emitted by the terahertz source (3) in each group passes through the ring-in sampling area of the movable ring (1) and reaches the corresponding side of the terahertz detector (4); The movable ring (1) can rotate relative to the fixed seat (2) at an angle of 0-180°; The pipeline defect detection method comprises the following steps: The polyethylene gas pipe is conveyed to the terahertz signal radiation area along the conveying belt; the terahertz signal radiation area is the ring-in sampling area of the movable ring (1); the movable ring (1) rotates circumferentially and reciprocally; The terahertz signal penetrates the polyethylene gas pipe; the terahertz signal carrying the gas pipe wall thickness and defect information is collected by the terahertz detector (4) and imaged, then transmitted to the computer (5) for image data processing and analysis, a three-dimensional model of the polyethylene gas pipe is established, and potential defects are visually displayed and marked; The image data processing and analysis process is as follows: ①The computer (5) obtains the conveying speed of the polyethylene gas pipe and the circumferential rotation speed of the movable ring (1); ②The three groups of terahertz detection components constitute channel one, channel two and channel three; the computer (5) simultaneously calculates the spatial orientation of the channel one scanning area, the spatial orientation of the channel two scanning area and the spatial orientation of the channel three scanning area at the current time, and simultaneously obtains the spectral data of the channel one scanning area, the spectral data of the channel two scanning area and the spectral data of the channel three scanning area at the current time; ③The spatial coordinate relationship of each discrete spectral data point of each channel is calculated to form a spectral-coordinate data point set of each channel; ④The spectral-coordinate data point sets of each channel are integrated to form a total pipeline spectral-coordinate data point set; ⑤The potential defect area discrimination algorithm is used to discriminate each coordinate in the total pipeline spectral-coordinate data point set to form a defect-coordinate data point set; ⑥The polyethylene gas pipeline quality cloud chart drawing algorithm is used to draw the polyethylene pipeline quality cloud chart; The potential defect area discrimination algorithm process is as follows: ①Read the terahertz detector (4) signal of each channel and input it into the program as the pipeline spectral-coordinate data point set; ②Analyze the pipeline spectral data of each channel to determine whether there is a defect inside the pipeline by using the time domain signal; ③Perform time-frequency conversion on the time domain spectral data, and input each frequency domain spectrum into the defect classification model for judgment; if the judgment is true, it is considered that the region where the discrete spectral data point is located contains a defect, and the defect depth regression model is used for defect depth calculation; if the judgment is false, it is considered that the region where the discrete spectral data point is located does not contain a defect; ④The discrimination results in the time and frequency domains are integrated to form a defect-coordinate data point set; In the detection process, the conveying speed of the polyethylene pipeline needs to be matched with the rotating speed of the dynamic ring (1) as the detection, and the speed relationship is as follows: ； Wherein: the polyethylene pipeline conveying speed is , the rotating angular velocity of the moving ring (1) is , the receiving range length of the terahertz detector (4) is , the diameter of the circumference where the terahertz detector (4) and the terahertz source (3) are located is , and the diameter of the polyethylene pipeline is ; The polyethylene gas pipeline quality cloud chart drawing algorithm is: ① input the current time polyethylene pipeline defect-coordinate data point set; ② draw the current time defect scatter plot of the overall area of the polyethylene pipeline; ③ draw the current time polyethylene pipeline quality cloud chart by using the bicubic interpolation algorithm; ④ draw the overall polyethylene pipeline quality cloud chart in combination with historical cloud chart data.

2. The method of claim 1, wherein The terahertz detector (4) of each terahertz detection component is respectively connected with the computer (5) signal.

3. The method of claim 1, wherein The time-frequency conversion is a fast Fourier transform algorithm.

4. The method of claim 1, wherein The rotating action of the dynamic ring (1) is driven by a servo motor or manually driven.

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