DESC:[0033] Brief description of the drawings
[0034] The foregoing and other features of embodiments will become more apparent from the following detailed description of embodiments when read in conjunction with the accompanying drawings. In the drawings, like reference numerals refer to like elements.
[0035] Figure 1illustrates a schematic representation of magnetic flux leakage inspection tool according to one embodiment of the present invention;
[0036] Figure 2illustrates a schematic representation of a drive section according to one embodiment of the present invention;
[0037] Figure 3illustrates a schematic representation of a CPU section according to one embodiment of the present invention;
[0038] Figure 4illustrates a schematic representation of a magnetic section according to one embodiment of the present invention;
[0039] Figure 5illustrates a schematic representation of an odometer according to one embodiment of the present invention; and
[0040] Figure 6illustrates a method flow diagram for inspection of oil and gas pipelines utilizing a magnetic flux leakage inspection tool.
[0041] Detailed description of the invention
[0042] Reference will now be made in detail to the description of the present subject matter, one or more examples of which are shown in figures. Each example is provided to explain the subject matter and not a limitation. Various changes and modifications obvious to one skilled in the art to which the invention pertains are deemed to be within the spirit, scope and contemplation of the invention.
[0043] Figure 1 illustrates a schematic representation of magnetic flux leakage inspection tool. The magnetic flux inspection tool essentially comprises of five sections for carrying out different functions of the tool and these sections are classified as drive section (3), magnetizer section (4), CPU (Central Processing Unit) section (5), battery section (6), and transmitter section (7). The drive section (3) mainly drives the magnetic flux leakage inspection tool by extending along inside the oil and gas pipeline and drives the tool inside the pipeline. The inspection tool is pulled from the front side rather than pushing from its back. The drive section (3) is heavy and carefully designed according to the meeting demands or applications of the magnetic flux leakage tool for inspection of pipelines. The cups (2) of rear sections of the inspection tool are bypassed and the pressure which comes from the rear side of the tool it is exerted on the cup (2) of the drive section (3). There are two cups in the drive section(3). One is a front cup and second one is a back cup. The pressure on the back cup is more than the pressure exerted on the front cup. The magnetizer section(4) comprises of usage of heavy magnets due to which magnetized field is formed and sensors are installed between the magnetized field so that when the inspection tool is pulled by the drive section(3) so that a continuous flow of magnetic field goes on. When there is a defect at any point of the inspection tool, this magnetic field gets deflected. Soon after deflection of magnetic field, the installed sensors will collect the magnetic field deflection data and store this data at one place. The sensors used for data storage are mainly of two types which are hall sensors and proximity sensors. Hall sensors detect the severity and type of defect in the tool and proximity sensors detects whether the defect is inside or outside the pipeline. This collected data by the sensors gets stored in the embedded system of the CPU section(5). The CPU section(5) comprises of an inertial navigation system. The saved data in CPU section(5) is pulled into the software using a USB (Universal Serial Bus) cable. This saved data is analyzed after which there is markation and demarkation of software and virtual reality reports are generated and submitted to the client.
[0044] Figure 2 illustrates a schematic representation of a drive section (3). The drive section (3) mainly drives the magnetic flux leakage inspection tool by extending along inside the oil and gas pipeline and drives the tool inside the pipeline. The inspection tool is pulled from the front side rather than pushing from its back. The drive section (3) is heavy and carefully designed according to the meeting demands or applications of the magnetic flux leakage tool for inspection of pipelines. The cups (2) of rear sections of the inspection tool are bypassed and the pressure which comes from the rear side of the tool it is exerted on the cup (2) of the drive section (3). There are two cups in the drive section (3). One is a front cup and second one is a back cup. The pressure on the back cup is more than the pressure exerted on the front cup.
[0045] Figure 3illustrates a schematic representation of a CPU section (5). The CPU section (5) comprises of an inertial navigation system. Inertial navigation system consists of an inertial measuring unit with an onboard computer with processing software installed or loaded on it. The software is able to access the inertial measuring unit data and reads the value of yaw, pitch and roll to create a 3D model of the plane of the in-line-inspection tool. This data after being processed by the software creates a visual of the plane of the in-line-inspection tool according to the earth’s surface plane as a reference plane and provides it’s orientation which can be used to determine the altitude and the size of the curves in pipelines and thus contributing to the defect detection by the in-line-inspection tool. The saved data in CPU section (5) is pulled into the software using a USB (Universal Serial Bus) cable. A strap down unit is provided in IMU that may contain three angular rotation sensors (gyroscopes), accelerometers and magnetometer mounted in three orthogonal axes. Gyroscopes measure angular changes while accelerometers measure acceleration and magnetometer measure automatic gyro bias compensation. The raw measurements from the IMU are recorded at a rate of multiple Samples per Second in the output of Roll, Pitch and Yaw and are time tagged with the System time. Data from the gyroscopes, accelerometers and magnetometer may be used by a post-processing Software program to compute the geographic coordinates, elevation and attitude of the tool during the inspection. An IMU may be used to determine three-dimensional changes in a pig's position on earth as the pig travels through a pipeline. IMU's measure the deflection of a pig as it rides over a bend in a pipeline. This data provides information regarding bends and other physical anomalies within a pipeline such as corrosion. The location of bends within Specific metal loss regions may be determined by correlating inertial deflection information with the in-line feature or defect detection or MFL data and tying accurate GPS coordinates to the data also. The inertial measuring unit consists of many types and although our product is not bounded to some particular parameters for type selection but for the sake of simplicity and accuracy, we are going with FOG (Fibre Optic Gyros) inertial measurement unit. The FOG-IMU consists of a light source such as a laser which emits light at a fixed frequency and some reflectors along with fibre cable. The light emitted by the laser source strikes the reflector and bounces back and by using fibre cables the light is travelled from the source to the detector. Based upon the time it is taken by the light to reach the detector sensor. The sensor can calculate the changes in the orientation of the product which in this particular case is an in-line-inspection tool or magnetic flux leakage pipeline inspection tool. The FOG-IMU uses a RS-422 standard for communicating with the embedded system’s core of the product which has 9 axes Degree-Of-Freedom (DOF). A 6 axes Degree of freedom (DOF) is also used along with the 9 axis to increase the accuracy of the inertial navigation system. As the pig moves in the pipe, a certain amount of error despite being minute gets introduced to the IMU readings and these errors keep on piling up one upon another and results in the direction drift of the inertial navigation system thus making the readings of the in-line-inspection tool redundant. The Inertial Measuring Unit consists of an accelerometer which provides the acceleration of the in-line-inspection tool, a gyrometer which detects the angular changes of the in-line-inspection tool and a magnetometer which improves the accuracy of the previous two by providing accurate measurements of the plane of the in-line-inspection tool according to the earth’s magnetic field plane and thus compensating the values accordingly the Inertial Measuring Unit provides the final values in the form of Yaw, Pitch and Roll which are used by the data processing software of the inertial navigation system to construct a 3-D visualization of the path taken by the in-line-inspection tool and by associating these coordinates with the Global Positioning System data and the in-line-inspection tool’s data the exact location of a defect and its size can be found out accurately with high precision values of plus or minus one meter. Control points are provided which are mainly the points that specify the location of an in-line inspection tool that can be identified both above and underground. A periodic series of control points are taken into consideration along a pipeline. In our invention, we recommend placing the control points at a distance of two to three km intervals, which saves a lot of time and manpower. Because of the decrease in control points used, the needed workforce is reduced and therefore, small crews can handle the setup operations. With the use of control points, the pipeline features can be detected easily by both sensors in the in-line inspection tool and can be identified visually on the Surface. Examples of such features may include valves, tees, cathodic protection anodes, bends. etc. AGM sites can be used as control points where no identifiable features are available, or AGM sites and identifiable features can both be used as control points along a pipeline. The procedure of the product is not restricted to any particular AGM. Generally, AGMs are portable devices that may include an accurate clock synchronized to the time in the in-line inspection tool, a magnetic sensor capable of detecting the magnetic field generated by the passage of the in-line inspection tool which consists of permanent or electromagnets and a recording system. When placed on the ground directly above the pipeline, the AGM will log the time the tool passes when the magnetic field sensor indicates that the tool has passed by. As the clocks in the AGM and the tool are synchronized, the position of the AGM in the tool data may be identified by examining the tool data at the time the AGM detected the passage of the tool. These are the points that specify the location of an in-line inspection tool that can be identified both above and underground. A periodic series of control points are taken into consideration along a pipeline. In our invention, we recommend placing the control points at a distance of two to three km intervals, which saves a lot of time and manpower. Because of the decrease in control points used, the needed workforce is reduced and therefore, small crews can handle the setup operations. With the use of control points, the pipeline features can be detected easily by both sensors in the in-line inspection tool and can be identified visually on the surface. Examples of such features may include Valves, tees, cathodic protection anodes, bends. etc.
[0046] Figure 4illustrates a schematic representation of a magnetic section (4). The magnetizer section (4) comprises of a large number of N52 magnetic grade permanent neodymium magnets with remanence of 1.437 Tesla or 14.35 kGs. These magnets are arranged in a horizontal manner around the outer circumference of the chamber and the core is shielded by harder steel (creusobro) plating are also used so that the magnets are in the close proximity of the pipeline’s inner surface as much as possible. The magnet chamber generates a strong magnetic field which is utilized by the hall effect sensor to detect any kind of anomaly on the pipeline’s inner surface. The magnetic field generated is also utilized by the above ground markers to detect when the pig has passed through them and to note down the time at that particular point and keep a record of it for analyzing the data of the in-line-inspection tool and adjust it according to it so as to reduce the amount and effect of errors introduced by the inertial measuring unit so that an accurate reading can be provided by the inertial navigation system.
[0047] Figure 5illustrates a schematic representation of an odometer (8). Odometer is used to measure the distance travelled by a tool. In this case, the tool has to measure the distance travelled by the in-line-inspection tool or MFL in the pipeline. By measuring the distance travelled by the in-line-inspection tool and associating this data with the data of Above Ground Markers (AGM), the calculation for the position of the defect detected by the in-line-inspection tool can be done and the position of the detected defect can be accurately pointed out. Odometer wheels use a mechanical wheel made by using stainless steel. These wheels move according to the displacement of the in-line-inspection tool and are used to calculate the distance travelled by the in-line-inspection tool. By linking this data with data of timer boxes or the Above Ground Markers (AGM) the speed of the in-line-inspection tool can be accurately calculated as the timer boxes provide the time in which the in-line-inspection moves from one marker to another and odometer wheels provide the distance travelled by the in-line-inspection tool.
[0048] Figure 6illustrates a method flow diagram for inspection of oil and gas pipelines utilizing a magnetic flux leakage inspection tool. The hardware part comprises of five sections and each of the said section contains two polyurethane cups. These five sections are drive section (3),magnet section (4), CPU section (5), battery section (6) and transmitter section (7). The magnet section (4) contains neodymium magnets of grade N-52 having strength of 1.435 Tesla and have number of hall sensors along which gives data at a speed of 1500 data/sec of each sensors along with customized proximity sensors for ID-OD data. The CPU section (5) contains the Printed circuit boards which are going to be used to gather the data from the sensors and collect the said data in SD cards with readable format. The CPU section (5) at the heart contains a FPGA (Field Programmable Gate Array) as the processing unit and this section also includes a 6-Axis IMU with GPS for the INS (Inertial Navigation System). The embedded systems 2019 used in the present invention makes the artificial intelligence core of the product. The battery section (6) contains the Li-Ion battery which serves as the power source for the present invention and also contains a 9-Axis IMU which provides precision to the INS data and thus makes it more reliable. Transmitter section (7) contains the transmitter to trace the tool moving in the pipeline and thus is beneficial in case our present invention gets stuck in pipeline. As per the software is concerned, machine learning is being used during the calibration process to make the readings being recorded are up to the mark and are precise. Once the tool is collected from the pipeline the data from the SD (Secure Digital) cards is collected by the big datasoftware available on a computer and the data is then stored along with the relevant information such as time for which the tool was in the pipeline, the date, the locations of the entry and exit and other related information too.The software is able to access the inertial measuring unit data and reads the value of yaw, pitch and roll to create a 3D model of the plane of the in-line-inspection tool. This data after being processed by the software creates a visual of the plane of the in-line-inspection tool according to the earth’s surface plane as a reference plane and provides its orientation which can be used to determine the altitude and the size of the curves in pipelines and thus contributing to the defect detection by the in-line-inspection tool. The big data software would then analyze the data and would then provide the data of defects (like corrosion, dent, pitting, metal losses, shrinkage) in the pipeline in a much more readable format in form of virtual reality which can be used by the client to found out the locations of those defects by using a mobile application. Once analyzed the data would be provided to the client in 10 days for dig verification which would be done using augmented reality.
[0049] The embedded system’s core of the in-line-inspection tools consists of an onboard memory which is used to store all the necessary data generated by the in-line-inspection tool. This memory is often of fast read and writes speeds as the data generated in a span of a second is of very high rate. The data stored by the data logger consists of the in-line-inspection tool data which contains the information about the defects detected by the MFL and this data is linked with the timer data of the embedded system and is also associated with the data of the global positioning system. This data thus provides a systematic manner by which using keys such as time, distance and position the exact readings of the in-line-inspection tool at these points can be recovered and used to provide sufficient details required for the calculation of the structural integrity of the pipeline. This data is used by the inertial navigation system and is verified by the timer boxes or AGM to pinpoint the exact location of the defect detected by the in-line-inspection tool with the accuracy of plus or minus one meters.
[0050] While the present invention is particularly shown and described with reference to exemplary embodiments thereof, it will be understood by those of ordinary skill in the art that various changes in form and details are made therein without departing from the spirit and scope of the present invention as defined by the following claims.

,CLAIMS:[0051] CLAIMS
We claim:
1. The magnetic flux leakage tool and method for inspection of oil and gas pipelines utilizing a magnetic flux leakage inspection tool, the method comprising the steps of:-
a) recording precise and up to the mark readings during the calibration process using machine learning;
b) collecting the data from the SD card with the big data software;
c) storing the data along with the relevant information in the software;
d) accessing the inertial measuring unit data and reading the value of yaw, pitch and roll by the software to create a 3D model of the plane of the in-line-inspection tool;
e) processing of the data by the software to create a visual of the plane of the in-line-inspection tool according to the earth’s surface plane as a reference plane;
f) providing orientation of the tool to determine the altitude and the size of the curves in pipelines;
g) analyzing the data by the algorithm in a particular software;
h) providing the data of defects in the pipeline in a much more readable format in form of virtual reality to be used by the client to find out the locations of these defects using a mobile application; and
i) providing the data to the client for dig verification which is achieved using augmented reality.

2. The magnetic flux leakage tool and method as claimed in claim 1, wherein thesoftware is able to access the inertial measuring unit data and reads the value of yaw, pitch and roll to create a visual 3D model of the plane of the in-line-inspection tool.

3. The magnetic flux leakage tool and method as claimed in claim 1, wherein the magnetizer section (4) comprises of a magnet chamber having a large number of N52 magnetic grade permanent neodymium magnets with remanence of 1.437 Tesla or 14.35 kGs.

4. The magnetic flux leakage tool and method as claimed in claim 1, wherein a strong magnetic field generated by the magnetizer section (4) is utilized by the Hall Effect sensor to detect any kind of anomaly on the pipeline’s inner and outer surfaces.

5. The magnetic flux leakage tool and method as claimed in claim 1, wherein the data is provided by a speed of 1500 data/second per sensor and approximately 2 lakh data /second is acquired.

6. The magnetic flux leakage tool and method as claimed in claim 1, wherein the large volume of data is being processed with embedded big data software.

7. The magnetic flux leakage tool and method as claimed in claim 6, wherein the data is used by the machine learning algorithm to assimilate the patterns and defects in pipelines, welded joints, valves etc.

8. The magnetic flux leakage tool and method as claimed in claim 7, wherein the patterns are assessed by artificial intelligence and sieving of the undesirable patterns.

9. The magnetic flux leakage tool and method as claimed in claim 7, wherein the data obtained is converted with a real map scenario and represented in the form of virtual reality which makes it easier to anatomize the data.

10. The magnetic flux leakage tool and method as claimed in claim 1, wherein the relevant information with the stored data comprises of time for which the tool was in the pipeline, the date, the locations of the entry and exit and other related information.

11. The magnetic flux leakage tool and method as claimed in claim 1, wherein the data of defects in the pipeline comprises of corrosion, dent, pitting, metal losses, shrinkage.