Intelligent leak detection system and leak detection method for ultra-large-scale space film type low-temperature storage tank

Abstract

The invention provides an intelligent leak detection system and leak detection method for a super-large-scale space film type low-temperature storage tank, and the system comprises an unmanned plane acoustic imaging subsystem, a leak comprehensive recognition and judgment subsystem, and the unmanned plane acoustic imaging subsystem can achieve the quick scanning of a detected region, and carries out the three-dimensional laser scanning. Sound field scanning is carried out on the detected area by using the sound imaging module; the leakage comprehensive identification and judgment subsystem under the unmanned aerial vehicle detection framework can perform three-dimensional reconstruction of a detection area based on laser scanning information and form a defect distribution three-dimensional image of the detection area by superposing sound field scanning information; through automatic scanning of the unmanned aerial vehicle in a detection area and leakage comprehensive identification and judgment under the unmanned aerial vehicle detection framework, automatic scanning and defect position three-dimensional imaging of the super-large-scale space film type low-temperature storage tank can be realized under the unmanned aerial vehicle framework, the detection working condition requirements are met, the requirements for the number and experience of detection personnel are reduced, and the detection efficiency is improved. And the detection efficiency and reliability are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of leakage detection, and in particular to an intelligent leakage detection system and a leakage detection method for a super-large-scale space thin-film type cryogenic storage tank. Background Art

[0002] Membrane type cryogenic storage tanks are key equipment for the shipping industry to achieve long-distance and efficient transportation of cryogenic liquefied gas. Vessels equipped with membrane type cryogenic storage tanks have many advantages, such as high utilization of cargo space, low evaporation rate, relatively low maintenance cost, and high safety. Currently, membrane type cryogenic storage tanks are the mainstream choice in the liquefied gas shipping industry.

[0003] Membrane type tanks consist of primary and secondary shielding layers, and primary and secondary insulation spaces (refer to Figure 1 ), the reason why the film-type cryogenic storage tank is called film-type is that the primary and secondary shielding layers are both made of film materials. The current mainstream film-type cryogenic storage tanks are divided into NO96 and Mark III. The primary and secondary shielding layers of the N096 type are both welded with 0.7mm thick Invar steel. The main shielding layer of the Mark III type is a 1.2mm thick corrugated plate, and the secondary shielding layer is a three-layer composite sheet about 0.6mm thick. The main shielding layer is in direct contact with the cryogenic liquefied gas. Therefore, ensuring the airtightness of the main and secondary shielding layers, especially the airtightness of the main shielding layer, is the top priority of quality control during the construction and operation and maintenance stages of the tank. In addition, the liquid dome is equipped with material holes and manholes to facilitate the entry and exit of equipment and personnel.

[0004] Leak detection technology is the key technology to ensure the tightness of the primary and secondary shielding layers. However, due to the large size and long welds of marine membrane-type cryogenic storage tanks, manual inspection consumes a lot of manpower and is limited by personnel experience, which brings new challenges to the controllability of inspection quality. Intelligent detection methods are used to create pressure differences in the primary and secondary shielding layers of membrane-type cryogenic storage tanks to form acoustic imaging detection conditions. UAVs are equipped with detection devices to scan welds and identify them through acoustic imaging technology to improve detection efficiency and reliability, thereby reducing dependence on personnel. Summary of the invention

[0005] The purpose of the present invention is to provide an intelligent leak detection system and a leak detection method for a super-large-scale space membrane type cryogenic storage tank.

[0006] In order to achieve the above object, the technical solution of the present invention is: An intelligent leak detection system for ultra-large-scale space membrane-type cryogenic storage tanks, characterized by comprising a drone acoustic imaging subsystem and a comprehensive leakage identification and judgment subsystem, The drone acoustic imaging subsystem includes a rotary-wing drone, which is provided with a laser imaging module, an acoustic imaging module and a communication module. The laser imaging module is used to scan the detection space to obtain terrain data, the acoustic imaging module is used to scan the weld area to identify defect information, and the communication module is used for communication and data transmission between subsystems. The comprehensive leakage identification and judgment subsystem includes an equipment control module and a data acquisition and analysis module. The equipment control module controls the start and stop of the laser imaging module and the acoustic imaging module. The data acquisition and analysis module is communicatively connected to the rotor UAV, and the data acquisition and analysis module interacts with the equipment control module.

[0007] The leak detection method using the intelligent leak detection system for ultra-large-scale space membrane-type cryogenic storage tanks is characterized by comprising the following steps: Step S1) confirm that the inspected part is pressurized or evacuated to the specified pressure, meets the acoustic imaging conditions, there is no foreign matter in the tank that affects the flight of the rotary-wing UAV, and the communication between the UAV imaging subsystem and the comprehensive leakage identification and judgment subsystem is normal; Step S2) The laser imaging module scans the detection area and transmits the terrain data back to the data acquisition and analysis module; Step S3) The leakage comprehensive identification and judgment subsystem forms a three-dimensional topographic map of the detection area through the topographic data, and the data acquisition and analysis module extracts the characteristic information of the weld area through data analysis to establish a three-dimensional model of weld distribution; Step S4) the leakage comprehensive identification and judgment subsystem plans the scanning path of the rotary-wing UAV based on the three-dimensional model of the weld distribution; Step S5) the acoustic imaging module scans the weld area and transmits the data back to the comprehensive leakage identification and judgment subsystem; Step S6) The data acquisition and analysis module processes the acoustic imaging results, identifies the defect locations, and superimposes the acoustic imaging results with the three-dimensional model of the weld distribution to form a three-dimensional image of the defect distribution.

[0008] Furthermore, step S3 includes the following steps: Step S31) classifying and dividing the welds; Step S32) presenting the weld distribution in three dimensions; Step S33) Establish a three-dimensional model of weld distribution.

[0009] Furthermore, the step S31 includes the following steps: Step S311) performing image convolution on the three-dimensional topographic map of the detection area; Step S312) Integrate the convolved image; Step S313) performing regional thresholding on the integrated image; Step S314) Weld fitting.

[0010] Furthermore, the step S6 includes: the leakage comprehensive identification and judgment subsystem performs quality judgment on the defect distribution three-dimensional image, If the quality is qualified, the return command is sent to the rotary wing drone. If the quality is unqualified, the unqualified area is selected and the process returns to step S4 to replan the scanning path of the rotary wing drone.

[0011] The present invention is used for rapid and intelligent leak detection of large-scale products such as membrane-type cryogenic storage tanks with a capacity of more than 20,000 cubic meters, such as membrane-type liquefied natural gas storage tanks, liquid ammonia storage tanks, and liquid ethane storage tanks. It can automatically scan the detection area through a drone, and has comprehensive leakage identification and judgment under the drone detection framework. It can realize automatic scanning and three-dimensional imaging of defect locations of ultra-large-scale space membrane-type cryogenic storage tanks under the drone framework, adapt to the detection working conditions, reduce the requirements on the number and experience of detection personnel, and improve detection efficiency and reliability. BRIEF DESCRIPTION OF THE DRAWINGS

[0012] Figure 1 It is a structural schematic diagram of a cryogenic storage tank; Figure 2 It is a schematic diagram of the detection implementation of the present invention; Figure 3 A flow chart for establishing a three-dimensional model of a weld for the present invention; Figure 4 This is a flow chart of automatic acoustic imaging detection of unmanned aerial vehicles of the present invention.

[0013] Reference numerals: 1 UAV acoustic imaging subsystem, 11 Rotor UAV, 12 Laser imaging module, 13 Acoustic imaging module, 14 Communication module, 2. Leakage comprehensive identification and judgment subsystem, 21 equipment control module, 22 data acquisition and analysis module, 3 cryogenic storage tanks, 31 primary shielding layer, 32 secondary shielding layer, 33 inner hull. DETAILED DESCRIPTION

[0014] The technical solution of the present invention will be described clearly and completely below in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0015] This embodiment discloses an intelligent leak detection system for ultra-large-scale space membrane-type cryogenic storage tanks, such as Figure 1As shown, the membrane type cryogenic storage tank 3 is an octagonal columnar cabin structure, including a main shielding layer 31, a secondary shielding layer 32 and an inner hull 33 which are arranged in sequence from inside to outside, a main insulation space 34 is between the main shielding layer 31 and the secondary shielding layer 32, a secondary insulation space 35 is between the secondary shielding layer 32 and the inner hull 33, and the inner side of the main shielding layer 31 is the cabin space, and the cabin space is loaded with cryogenic liquefied gas during the operation stage.

[0016] The intelligent leak detection system of this embodiment includes a drone acoustic imaging subsystem 1 and a comprehensive leakage identification and judgment subsystem 2. The drone acoustic imaging subsystem 1 includes a rotor drone 11. The rotor drone 11 enters the cabin when it is running. The rotor drone 11 is provided with a laser imaging module 12, an acoustic imaging module 13 and a communication module 14. The laser imaging module 12 scans the detection space in the cabin to obtain terrain data, the acoustic imaging module 13 scans the weld area in the cabin to identify defect information, and the communication module 14 is used for communication and data transmission between subsystems.

[0017] The comprehensive leakage identification and judgment subsystem 2 is located on the outside of the inner hull 33. The comprehensive leakage identification and judgment subsystem 2 includes an equipment control module 21 and a data acquisition and analysis module 22. The equipment control module 21 controls the start and stop of the laser imaging module 12 and the acoustic imaging module 13. The data acquisition and analysis module 22 is communicated with the rotor UAV 11, and the data acquisition and analysis module 22 interacts with the equipment control module 21.

[0018] A leak detection method using an intelligent leak detection system for a super-large-scale space membrane type cryogenic storage tank comprises the following steps: Step S1) The primary insulation space 34 and the secondary insulation space 35 of the cryogenic storage tank are simultaneously evacuated to -800 mbar through the external interface. After confirming that the pressure meets the standard, the valve at the external interface is closed; Confirm that the cryogenic storage tank is capable of acoustic imaging and that there are no foreign objects inside that may affect the flight of the rotary-wing UAV 11; Confirm that the communication between the UAV imaging subsystem 1 and the comprehensive leakage identification and judgment subsystem 2 is normal.

[0019] Step S2) Figure 2 As shown, the rotor UAV 11 is manually started to enter the cabin. After the rotor UAV 11 hovers stably, the laser imaging module 12 is started to detect the starting point coordinates. The laser imaging module 12 scans the inside of the cryogenic storage tank. During the scanning process, the rotor UAV 11 transmits data back to the leakage comprehensive identification and judgment subsystem 2.

[0020] Step S3) Figure 3 As shown, the leakage comprehensive identification and judgment subsystem 2 forms a three-dimensional topographic map of the space inside the cryogenic storage tank through the topographic data, and the data acquisition and analysis module 22 extracts the characteristic information of the weld area through data analysis to establish a three-dimensional model of the weld distribution; Step S3 includes the following steps: Step S31) classifying and dividing the welds; Step S32) presenting the weld distribution in three dimensions; Step S33) Establish a three-dimensional model of weld distribution.

[0021] Step S31 includes the following steps: Step S311) performing image convolution on the three-dimensional topographic map of the detection area; Step S312) Integrate the convolved image; Step S313) performing regional thresholding on the integrated image; Step S314) Weld fitting.

[0022] Step S4) the leakage comprehensive identification and judgment subsystem 2 plans the scanning path of the rotary-wing UAV 11 according to the three-dimensional model of the weld distribution; Step S5) The acoustic imaging module 13 scans the weld area and transmits the data back to the leakage comprehensive identification and judgment subsystem 2; during the scanning process of the rotor UAV 11, the acoustic imaging signal of the acoustic imaging module 13 is continuously transmitted back, and after signal preprocessing, a sound field image containing defect information is formed.

[0023] Step S6) The data acquisition and analysis module 22 processes the acoustic imaging results, identifies the defect locations, and superimposes the acoustic imaging results with the three-dimensional model of weld distribution to form a three-dimensional image of defect distribution.

[0024] Step S6 includes, the acoustic imaging module 13 performs quality judgment on the defect distribution three-dimensional image, If the quality is qualified and confirmed to be correct, a return command is sent to the rotor drone 11. If the quality is unqualified, the unqualified area is selected and the process returns to step S4 to replan the scanning path of the rotary-wing drone 11.

[0025] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or replace some or all of the technical features therein with equivalents. However, these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. An intelligent leak detection system for ultra-large-scale space membrane-type cryogenic storage tanks, characterized in that: It includes a drone acoustic imaging subsystem (1) and a comprehensive leakage identification and judgment subsystem (2). The drone acoustic imaging subsystem (1) comprises a rotary-wing drone (11), wherein the rotary-wing drone (11) is provided with a laser imaging module (12), an acoustic imaging module (13) and a communication module (14), wherein the laser imaging module (12) is used to scan a detection space to obtain terrain data, the acoustic imaging module (13) is used to scan a weld area to identify defect information, and the communication module (14) is used for communication and data transmission between subsystems. The comprehensive leakage identification and judgment subsystem (2) comprises an equipment control module (21) and a data acquisition and analysis module (22); the equipment control module (21) controls the start and stop of the laser imaging module (12) and the acoustic imaging module (13); the data acquisition and analysis module (22) is communicatively connected with the rotary-wing UAV (11); and the data acquisition and analysis module (22) interacts with the equipment control module (21).

2. A leak detection method using the intelligent leak detection system for ultra-large-scale space membrane-type cryogenic storage tanks according to claim 1, characterized in that: The following steps are involved: Step S1) confirming that the inspected part is pressurized or evacuated to a specified pressure, meets the acoustic imaging conditions, there is no foreign matter in the tank that may affect the flight of the rotary-wing UAV (11), and the communication between the UAV imaging subsystem (1) and the comprehensive leakage identification and judgment subsystem (2) is normal; Step S2) the laser imaging module (12) scans the detection area and transmits the topographic data back to the data acquisition and analysis module (22); Step S3) the leakage comprehensive identification and judgment subsystem (2) forms a three-dimensional topographic map of the detection area through the topographic data, and the data acquisition and analysis module (22) extracts the characteristic information of the weld area through data analysis to establish a three-dimensional model of the weld distribution; Step S4) the leakage comprehensive identification and judgment subsystem (2) plans a scanning path of the rotary-wing UAV (11) based on the three-dimensional model of the weld distribution; Step S5) the acoustic imaging module (13) scans the weld area and transmits the data back to the comprehensive leakage identification and judgment subsystem (2); Step S6) The data acquisition and analysis module (22) processes the acoustic imaging results, identifies the defect locations, and superimposes the acoustic imaging results with the three-dimensional model of weld distribution to form a three-dimensional image of defect distribution.

3. The leak detection method according to claim 2, characterized in that: The step S3 comprises the following steps: Step S31) classifying and dividing the welds; Step S32) presenting the weld distribution in three dimensions; Step S33) Establish a three-dimensional model of weld distribution.

4. The leak detection method according to claim 3, characterized in that: The step S31 comprises the following steps: Step S311) performing image convolution on the three-dimensional topographic map of the detection area; Step S312) Integrate the convolved image; Step S313) performing regional thresholding on the integrated image; Step S314) Weld fitting.

5. The leak detection method according to claim 2, characterized in that: The step S6 includes: the leakage comprehensive identification and judgment subsystem (2) performs quality judgment on the defect distribution three-dimensional image, If the quality is qualified, a return command is sent to the rotary wing drone (11). If the quality is unqualified, the unqualified area is selected and the process returns to step S4 to replan the scanning path of the rotorcraft drone (11).

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