CN112229900A - A flexible intelligent pipeline defect detection device - Google Patents

Abstract

The invention discloses a flexible intelligent pipeline defect detection device which comprises a driving robot, a system controller, a power supply, a multi-signal collector, a data processor, a position tracker, a connection structure, an infrared distance sensor and an equipment peripheral structure. The power supply is responsible for supplying power for each structure, the whole pipeline defect detection device is pulled to advance by the driving robot, the multi-signal collector collects signals, data are digitized and stored in the data processor, a data fusion center in the data processor obtains a compensated defect signal through a data fusion algorithm, fusion is further achieved through Kalman filtering, self-adaptive weighted averaging or principal component analysis, and more accurate information of depth, width, length and the like of the defect is obtained. The position tracker is used for tracking and recording the defect position in real time. The invention has the advantages of high measurement precision, small size, intelligent detection, strong adaptability to complex pipelines and the like.

Description

Flexible intelligent pipeline defect detection device

Technical Field

The invention belongs to the field of nondestructive testing, and particularly relates to a flexible intelligent pipeline defect detection device.

Background

Along with the increase of oil gas pipeline service life, ageing phenomenon is serious day by day, and buried pipeline is located the environment very abominable, the topography is extremely complicated and influence such as artificial destruction, construction defect and corruption, and pipeline leakage accident frequently takes place, not only brings the leakage loss such as oil, gas, still can bring the wasting of resources because of the maintenance, and the shut down stops production and causes economic loss, can cause very big pollution to the environment moreover. Therefore, the method is very necessary for timely detecting the defects, and the detection result is an important basis for pipeline maintenance. The magnetic leakage detection is a high-efficiency oil and gas pipeline detection method at present, a magnetic leakage sensor working in an oil and gas pipeline collects magnetic leakage data, and the information is processed and analyzed to determine the conditions of defects, corrosion and the like of the pipeline.

Because the pipeline internal sensor is more, and the data bulk of gathering is very big, so need one be used for automatic processing, analysis and detection data, aassessment quantization pipeline defect, show the intelligent device of testing result, intelligent pipeline detector not only can automatic analysis magnetic leakage data, can show the magnetic leakage data for testing personnel with the form of imaging moreover, testing personnel can look over the change of magnetic leakage data directly perceivedly, aassessment, location pipeline defect fast accurately.

Disclosure of Invention

Aiming at the defects of the prior art, the invention aims to provide a flexible intelligent pipeline defect detection device taking magnetic flux leakage detection as a theoretical core.

The invention is realized by the following technical scheme: a flexible intelligent pipeline defect detection device is composed of a driving robot, a system controller, a power supply module, a multi-sensor module, a data processor, a position tracker and a connecting structure; the method is characterized in that: the driving robot, the system controller, the power supply module, the multi-sensor module, the data processor and the position tracker are connected by adopting a connecting structure; the power supply module supplies power to other modules; the position tracker is used for tracking and recording the defect position in real time; the multi-sensor module is a plurality of Hall sensor groups capable of detecting magnetic flux changes and consists of a magnetic flux leakage axial sensor, a magnetic flux leakage circumferential sensor, a temperature sensor, a speed sensor, a pipeline pressure sensor and a magnetizing device; the driving robot is located the place ahead of whole device, and infrared distance sensor is used for detecting the environmental data of pipeline, distance data submit to the system control ware, and auxiliary system controller control driving robot pulls whole device and gos forward, and the multisensor module gathers multiple signal, digitizes data and saves data processor, and data processor obtains the defect signal of a compensation through data fusion algorithm, and then obtains more accurate information such as defect degree of depth, width, length, shape through the analysis.

The connecting structure is a wire which is packaged and connected with each module and is used for transmitting data and controlling.

The working principle of the invention is as follows: when the device is used for detecting in a pipeline, the magnetizing device generates a standard magnetic field, the ferromagnetic pipeline is magnetized at the moment, and when the pipeline has no defects, the magnetic field lines are uniformly distributed in the pipeline, and the leaked magnetic flux is about zero. When the pipeline is damaged, the magnetic permeability of the defect part is small, the magnetic resistance is large, the magnetic flux in the magnetic circuit is distorted, part of the magnetic flux leaks to form a leakage magnetic field, and relevant characteristic information of the defect can be obtained from the optimized signal of the leakage magnetic through the acquisition and signal processing of the leakage magnetic signal.

The invention has the beneficial effects that: the full-automatic pipeline defect detection can be realized through the design of a driving robot in the device. When the conductive material moves rapidly in the magnetic field, the current in the conductor can generate a motion induced current, so that the magnetic field is formed to cause interference, and the interference can be influenced under different temperature and pressure conditions. A multi-sensor data fusion technology is designed, the acquired defect signals are effectively compensated, more accurate leakage magnetic field signals are obtained, and the compensated defect signals are analyzed through a neural network, so that more accurate defect characteristic information and a three-dimensional contour model are obtained.

Drawings

FIG. 1 is a diagram of a flexible intelligent pipeline defect detection device.

FIG. 2 is a schematic diagram of signal processing of a flexible intelligent pipeline defect detection device.

FIG. 3 is a schematic diagram of a data fusion algorithm of the flexible intelligent pipeline defect detection device.

FIG. 4 is a schematic diagram of a flexible intelligent pipeline defect detection device during detection of a bent pipeline.

Detailed Description

As shown in fig. 1, a flexible intelligent pipeline defect detecting device is composed of a driving robot 1, asystem controller 2, apower module 3, amulti-sensor module 4, adata processor 5, aposition tracker 6 and aconnecting structure 7; the method is characterized in that: the driving robot 1, thesystem controller 2, thepower supply module 3, themulti-sensor module 4, thedata processor 5 and theposition tracker 6 are connected by adopting aconnecting structure 7; thepower supply module 3 supplies power to other modules; theposition tracker 6 is used for tracking and recording the defect position in real time; themulti-sensor module 4 is a plurality of Hall sensor groups capable of detecting magnetic flux changes, and consists of a magnetic flux leakageaxial sensor 18, a magnetic flux leakagecircumferential sensor 17, atemperature sensor 19, aspeed sensor 20, apressure sensor 21 and a magnetizing device; the driving robot 1 is located in front of the whole device, theinfrared distance sensor 9 is used for detecting environmental data of a pipeline, the distance data are submitted to thesystem controller 2, theauxiliary system controller 2 controls the driving robot 1 to pull the whole device to move forward, themulti-sensor module 4 collects various signals to eliminate magnetic field interference generated by factors such as internal conductor current and the like, then the data are digitized, preprocessed and stored in thedata processor 5, thedata fusion center 23 in thedata processor 5 obtains a compensated defect signal through a data fusion algorithm, and then more accurate information such as defect depth, width, length, shape and the like is obtained through neural network analysis.

As shown in fig. 2, a plurality of leakagemagnetic signals 9 collected by themulti-sensor module 4 are subjected to data preprocessing 10, then are classified 11 into pipeline component signals and defect signals, the defect signals are subjected tosignal compensation 12, the compensated defect signals are represented by using a neural network algorithm to formdefect characteristics 14, safety evaluation is performed according to thedefect characteristics 14, and the pipeline component signals and the defect characteristics are used together to form a defectgraphic display 13.

As shown in fig. 3, when thepipeline inspection 16 is performed, signal data collected by the magnetic leakagecircumferential sensor 17, the magnetic leakageaxial sensor 18, thetemperature sensor 19, thespeed sensor 20, and thepressure sensor 21 are subjected to data preprocessing 22 methods such as time-frequency analysis, denoising, interpolation processing, and the like, and are fused by kalman filtering, adaptive weighted average, or principal component analysis when entering thedata fusion center 23, and a compensated defect signal is finally output.

Claims (2)

1. A flexible intelligent pipeline defect detection device is composed of a driving robot (1), a system controller (2), a power supply (3), a multi-signal collector (4), a data processor (5), a position tracker (6), a connecting structure (7), an infrared distance sensor (9) and an equipment peripheral structure (10); the method is characterized in that: the multi-signal collector (4) consists of a magnetic leakage axial sensor (20), a magnetic leakage circumferential sensor (19), a temperature sensor (21), a speed sensor (22), a pressure sensor (23) and a magnetizing device; the driving robot (1), the system controller (2), the power supply (3), the multi-signal collector (4), the data processor (5) and the position tracker (6) are all connected by adopting a connecting structure (7), the infrared distance sensor (9) is welded at the foremost end of the device, and an equipment peripheral structure (10) is used for surrounding the whole equipment; the equipment peripheral structure (10) and the connecting structure (7) are both made of flexible materials; the driving robot (1) is located in front of the whole device, the infrared distance sensor (9) is used for detecting environment data of a pipeline, distance data are submitted to the system controller (2), the auxiliary system controller (2) controls the driving robot (1) to pull the whole device to advance, the multi-signal collector (4) collects various characteristic signals from the pipeline wall (8) so as to eliminate magnetic field interference generated by factors such as current generated by conductor movement inside, then the data are digitized, preprocessed and stored in the data fusion center (25) of the data processor (5), a compensated defect signal is obtained through a data fusion algorithm, and then more accurate information such as defect depth, width, length, shape and the like is obtained through neural network analysis.

2. The miniature flexible intelligent pipeline defect detection device of claim 1, wherein: the flexible material is made of flexible ceramic material containing zirconium oxide and is used as a connecting structure (7) and a peripheral structure (10) of the equipment.

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