The present disclosure relates to the technical field of fluid leakage
detection, and in particular, to a system and method for detecting fluid leakage in a pipeline installed on a large area, and transporting oil, natural gas, or water.
BACKGROUND
[0002] The background description provided herein is for the purpose of
generally presenting the context of the disclosure. Work of the presently named inventors, to the extent the work is described in this background section, as well as aspects of the description that may not otherwise qualify as prior art at the time of filing, are neither expressly nor impliedly admitted as prior art against the present disclosure.
[0003] Pipelines are a widely used source for transportation of oil and gas
worldwide. However, incidents of oil and gas pipeline failures are becoming rather frequent, causing large financial costs, environmental damages, and health risks. One cause of the incidents is due to a lack of accurate methods of inspection for oil and gas pipelines. Techniques and systems have been developed to monitor underground and above-ground pipelines. However, most of the systems are localized to a limited area and function as a single localized unit. Therefore, a total length of monitored pipeline may be less than a total length of unmonitored pipeline. In addition, the techniques can also be applied to a localized area and the data is not sufficient to ensure a safety and maintenance of underground and above-ground pipelines. Also, individual nodular data is frequently separated and evaluated by human-monitored platforms.
[0004] Current leak detection systems for pipelines, for example, are costly
and are very-slow to implement. Some systems take six to nine months to install, for example. After the install, if there is a change made to the pipeline, it can take another four to six months to make the changes to the leak detection system. Various previous leak detection systems work off of hydro models which take time to develop and require each section of the pipeline to be modelled with its characteristics. When installing a typical prior art leak detection system, for

example, the installation becomes pipeline-segment specific, and if there are any
changes on a segment of the pipeline it may take up to six months to redeploy the
leak detection system.
[0005] There is, therefore, a need in the art to provide an efficient solution
that can obviate the above mentioned limitations, and provides a system and method
for detecting leakage in a pipeline and reducing casualty by notifying concerned
authorities.
OBJECTS OF THE PRESENT DISCLOSURE
[0006] A general object of the present disclosure is to obviate the above-
mentioned problems and assists in monitoring leakage in pipelines.
[0007] An object of the present disclosure is to detect leaks over a greater
portion of a pipeline.
[0008] An object of the present disclosure is to provide a system for
leakage detection that is easy to install or use, and do not require special (e.g., pipeline modelling) skill to use, install, or implement, detect smaller leaks, and avoid false positives.
[0009] Another object of the present disclosure is to provide a system to
notify nearby people in case of flammable leakage and reduce causalities.
[0010] Another object of the present disclosure is to provide a system to
notify onsite engineer/concerned person available at the location of leakage or main control room.
[0011] Another object of the present disclosure is to provide a system that
reduce cost of monitoring and maintenance.
SUMMARY
[0012] Various aspects of the present disclosure relates to fluid leakage
detection, and in particular, the present disclosure relates to a system and method for detecting fluid leakage in a pipeline installed on a large area, and transporting oil, natural gas, or water.

[0013] According to an aspect, the present disclosure a leakage detection
system for pipeline is disclosed. The system may include image acquisition unit(s) positioned along a length of pipeline transporting a fluid, wherein each of the plurality of image acquisition unit(s) configured to acquire one or more images of a pre-defined area of the pipeline, and storing the acquired one or more images in a first dataset, a location identifier(s) may be configured to acquired location information of each of the image acquisition unit(s), a control unit operatively coupled to the first dataset and the location identifier.
[0014] In an aspect, the control unit may be configured to receive the one
or more images from a first dataset, extract leakage-related data from the received one or more images using one or more learning techniques, receive location information of the associated image acquisition unit from the associated location identifier, upon detection of leakage-related data in the pipeline, classify the extracted leakage-related data to determine type and size of the leakage, and generating a warning signal pertaining to size of the leakage and location information of the leakage, wherein the generated warning signal is transmitted to one or more mobile computing devices.
[0015] In an aspect, each of the image acquisition unit may include an
image capturing unit and an image processing unit, and the image processing unit include a visual geometry group (VGG) to process the one or more images by performing image classification and feature extraction.
[0016] In an aspect, the leakage-related data includes pressure, temperature,
corrosion, and stress inside the pipeline.
[0017] In an aspect, the control unit may be configured to transmit an alert
signal to at least one alert unit positioned in an area where flammable type leakage detected in the pipeline.
[0018] In an aspect, one or more communication units may be configured
to establish communication in between the plurality of image acquisition units, each of the location identifier(s), and the one or more mobile computing devices.

[0019] In an aspect, the one or more communication units may include any
or a combination of GSM module, Wireless Fidelity (Wi-Fi) Module, Wireless
Local Area Network (WLAN), Bluetooth, Li-Fi Module and Zigbee.
[0020] In an aspect, the pipeline may include any or a combination of
underground pipeline, and the above-ground pipeline.
[0021] In an aspect, the pipeline may transport the fluid gas, oil, water, or
combination thereof.
[0022] Another aspect of the present disclosure pertains to a method for
monitoring a pipeline, the method acquiring, one or more images of a pre-defined
area of the pipeline, by a plurality of image acquisition units, extracting and
processing leakage-related data from the one or more images, by a control unit,
classifying the leakage-related data to determine size of the leakage, receiving
location information of the associated image acquisition unit upon detection of the
leakage in the pipeline, and transmitting, a warning signal pertaining to size and
type of the leakage and location information of the leakage to one or more mobile
computing devices by one or more communication units.
[0023] In an aspect, upon detection of flammable leakage from the pipeline,
at least one alert unit positioned in the area where leakage found actuated to produce
acoustic signal.
[0024] Various objects, features, aspects and advantages of the inventive
subject matter will become more apparent from the following detailed description
of preferred embodiments, along with the accompanying drawing figures in which
like numerals represent like components.
BRIEF DESCRIPTION OF THE DRAWINGS
[0025] The accompanying drawings are included to provide a further
understanding of the present disclosure, and are incorporated in and constitute a part of this specification. The drawings illustrate exemplary embodiments of the present disclosure and, together with the description, serve to explain the principles of the present disclosure.

[0026] FIG. 1 illustrates an exemplary block diagram of the proposed
system, in accordance with an exemplary embodiment of the present disclosure.
[0027] FIG. 2 illustrates an exemplary functional components of a
processing unit of the proposed system, in accordance with an exemplary embodiment of the present disclosure.
[0028] FIG. 3 illustrates an exemplary method in order to explain its
working, in accordance with an exemplary embodiment of the present disclosure.
DETAILED DESCRIPTION
[0029] The following is a detailed description of embodiments of the
disclosure depicted in the accompanying drawings. The embodiments are in such details as to clearly communicate the disclosure. However, the amount of detail offered is not intended to limit the anticipated variations of embodiments; on the contrary, the intention is to cover all modifications, equivalents, and alternatives falling within the spirit and scope of the present disclosures as defined by the appended claims.
[0030] Embodiments explained herein relate to the field of fluid leakage
detection. In particular, the present disclosure provides system and method for detecting fluid leakage in a pipeline installed on a large area, and transporting oil, natural gas, or water.
[0031] Embodiments herein describe a system to be attached with the
pipeline to detect leakage in the pipeline. The embodiments can be used for an
above-ground pipeline transportation or a buried pipeline transportation
infrastructure, wherein the buried pipeline infrastructure can be located below the
ground surface, below a water surface, or within a deep or buried enclosure below
a surrounding ground level. The pipeline can be designed and configured to carry
fluid such as water, oil, gas, or other liquid material across a spanned distance.
[0032] Exemplary fluid may be any suitable material that may be
transported via the pipeline. For example, the fluid may be a fossil fuel in fluid form (e.g., refined oil or crude oil, natural gas, and/or any other suitable type of fossil fuel), water, air, oxygen, carbon dioxide, and any suitable chemical in fluid form,

waste or wastewater, and/or any other suitable material that may flow through the pipeline.
[0033] FIG. 1 illustrates an exemplary block diagram of the proposed
system in order to explain its working, in accordance with an exemplary embodiment of the present disclosure.
[0034] As illustrated in FIG. 1, an exemplary leakage detection system 100
(interchangeably referred as system 100, hereinafter) for monitoring leakage in a pipeline. For example, system 300 may be any suitable system for pipeline monitoring (e.g., when pipeline is such as, e.g., an oil pipeline, a natural gas pipeline, any pipeline transporting fossil fuels, a water pipeline, a waste or wastewater pipeline, a pipeline transporting oxygen, carbon dioxide, air, chemicals, and/or any other fluid such as gaseous fluid or liquid fluid material). The system 100 can include a plurality of image acquisition units 102 (collectively referred as image acquisition units 102, and individually referred as image acquisition unit 102). Each of the image acquisition unit 102 can include an image capturing unit 104 and an image processing unit 106.
[0035] The image capturing unit 104 can be a camera, webcam, and the
likes that can be used to capture one or more images (or videos) (interchangeably referred as images, hereinafter) of the pipeline. Each of the image capturing unit 104 can be positioned on inside wall of the pipeline, and can be position to collect images of a pre-defied area. Each of the image capturing unit 104 can be positioned on a distance, such that inside images of entire pipeline can be collected and stored in a first dataset.
[0036] The image processing unit 106 can include a visual geometry group
(VGG) to process the one or more images by performing image classification and feature extraction. Image pixels may be the image input supplied by the image capturing unit 104 to the image processing unit 106. Since the image pixels may not be directly inputted into a deep learning model, the image processing unit 106 such as the VGG16, can be used to pre-process the image pixels. The processed images may be stored in the first dataset, and can be transmitted to a control unit 110 after a pre-defined time.

[0037] In an embodiment the system 100 can include a plurality of location
identifiers 108 (collectively referred as location identifiers 108, and individually referred as location identifier 108) i.e. GPS module (Global Positioning system), that can be configured to collect location information i.e. location coordinate of the area where the image acquisition unit is installed. Each of the location identifier 108 can be installed with an image acquisition unit 102.
[0038] In an embodiment, the control unit 110 can be operatively coupled
to the first dataset and each of the location identifier 108. The control unit 110 can be configured to receive the images from a first dataset, extract leakage-related data from the received images using one or more learning techniques, and receive location information of the associated image acquisition unit 102 from the associated location identifier 108. Upon detection of leakage-related data in the pipeline, classify the extracted leakage-related data to determine type and size of the leakage, and generating a warning signal.
[0039] In an embodiment, the warning signal can pertain type and size of
the leakage and location information of the leakage, and the generated warning signal can be transmitted to one or more mobile computing devices associated with on-site engineer and concerned authorities via one or more communication units 114 (interchangeably referred as the communication unit 114, hereinafter). The communication unit 114 can include any or a combination of GSM module, Wireless Fidelity (Wi-Fi) Module, Wireless Local Area Network (WLAN), Bluetooth, Li-Fi Module and Zigbee to transmit warning signals from the control unit to the associated mobile computing devices. The one or more mobile computing devices can include display monitors, smart phones, tablets, personal digital assistants (PDAs), and the likes.
[0040] In an embodiment, the system 100 can include at least one or alert
unit 112, where each of the alert unit 112 can be position with each of the image acquisition unit 112. Upon detection of flammable type leakage in the area, the associated alert unit 112 can receive alert signals from the control unit 110. The alert unit 112 can produce acoustic signals to notify nearby people to vacant the area at earliest. It can be buzzer, horn, LEDs, and the likes.

[0041] In an embodiment, the system 100 can include a power source (not
shown) that can contemplated including, but not limited to, rechargeable battery, NiCad battery, lithium (Li) ion cell, rechargeable cells, solar cell, solar battery, electrochemical cells, storage battery, secondary cell, etc. The power source can be operatively coupled to supply electricity to the image acquisition units 102, location identifiers 108, the control unit, and the alert units 112.
[0042] FIG. 2 illustrates an exemplary functional components of a
processing unit of the proposed apparatus, in accordance with an embodiment of the present disclosure.
[0043] As illustrated in FIG. 2, a control unit 110 can include one or more
processor(s) 202. The one or more processor(s) 202 can be implemented as one or
more microprocessors, microcomputers, microcontrollers, digital signal processors,
central processing units, logic circuitries, and/or any devices that manipulate data
based on operational instructions. Among other capabilities, the one or more
processor(s) can be configured to fetch and execute computer-readable instructions
stored in a memory of the control unit 110. The memory 204 can store one or more
computer-readable instructions or routines, which may be fetched and executed to
create or share the data units over a network service. The memory 204 can include
any non-transitory storage device including, for example, volatile memory such as
RAM, or non-volatile memory such as EPROM, flash memory, and the like.
[0044] In an embodiment, the control unit 110 can also include an
interface(s) 206. The interface(s) can include a variety of interfaces, for example, interfaces for data input and output devices, referred to as I/O devices, storage devices, and the like. The interface(s) 206 may facilitate communication of the control unit 110 with various devices coupled to the control unit 110. The interface(s) 206 may also provide a communication pathway for one or more components of processing unit. Examples of such components include, but are not limited to, processing engine(s) and database.
[0045] In an embodiment, a processing engine(s) 208 can be implemented
as a combination of hardware and programming (for example, programmable instructions) to implement one or more functionalities of the processing engine(s)

208. In examples described herein, such combinations of hardware and
programming may be implemented in several different ways. For example, the
programming for the processing engine(s) 208 may be processor executable
instructions stored on a non-transitory machine-readable storage medium and the
hardware for the processing engine(s) 208 may include a processing resource (for
example, one or more processors), to execute such instructions. In the present
examples, the machine-readable storage medium may store instructions that, when
executed by the processing resource, implement the processing engine(s) 208. In
such examples, the control unit 110 can include the machine-readable storage
medium storing the instructions and the processing resource to execute the
instructions, or the machine-readable storage medium may be separate but
accessible to the control unit 110 and the processing resource. In other examples,
the processing engine(s) may be implemented by electronic circuitry.
[0046] In an embodiment, the processing engine(s) 208 can include an
extraction unit 212, an image processing and classification unit 214, a comparison unit 216, a signal generation unit 218, and other unit(s) 220. The other unit(s) 220 can implement functionalities that supplement applications or functions performed by the system 100 or the processing engine(s) 208.
[0047] In an embodiment, a database 210 can include data that is either
stored or generated as a result of functionalities implemented by any of the components of the processing engine(s) 208.
[0048] It would be appreciated that units being described are only
exemplary units and any other unit or sub-unit may be included as part of the system 100. These units too may be merged or divided into super- units or sub-units as may be configured.
[0049] In an embodiment, the processing engine(s) 208 can be configured
to receive a first setoff signals pertaining one or more images of a pre-defined area of the pipeline from a plurality of image acquisition units in an electric form, and further transmits the first set of signals to the extraction unit 212. The extraction unit 212 can be configured to extract leakage-related data from the received one or

more images using one or more learning techniques. The leakage-related data
include pressure, temperature, corrosion, and stress inside the pipeline.
[0050] In an embodiment, the one or more learning techniques can include
deep learning algorithms, but not limited to such as support vector machines, decision trees, artificial neural networks, and convolutional neural networks (CNN).
[0051] In an embodiment, the control unit 110 can be configured to further
transmit the received images in machine readable form or binary form to the image processing and classification unit 214, where the one or more features can be extracted and classified to detect type of leakage, and the size of leakage. Further, the image processing and classification unit 214 can be updated and trained based on extracted features. In another embodiment, the image processing and classification unit 214 can be trained and updated based on the received images. A deep leaning model can be trained based on the received images to analyse the leakage, where the deep leaning model can be stored in the database 210. In yet another embodiment, once the database 210 is trained correctly, a deep learning algorithm can be used to perform repetitive, and routine tasks within a shorter period of time.
[0052] In an embodiment, the image processing and classification unit 214
can be configured to store the image processing and classification unit 214 of many
users recorded over a period of time for trend analysis and prediction of future risk.
Also, the image processing and classification unit 214 can be configured to store a
set of training datasets in the second dataset to train a machine learning model for
determining leakage automatically. The second dataset can include historical
information related to various type of leakage in the pipelines.
[0053] In an exemplary embodiment, the processing engine(s) 208 can be
further configured in the form of a learning engine like the following, but not limited to machine learning algorithms and deep learning algorithms. In an exemplary embodiment, the processing engine(s) 208 can include deep learning algorithms such as but not limited to support vector machines, decision trees, artificial neural networks, and convolutional neural networks.

[0054] In an embodiment, the comparison unit 216 can be configured to
compare the extracted leakage-related data with the pre-defined second dataset
storing the leakage images. Upon detection of size and type of leakage in the
pipeline, the signal generation unit 218 can be configured generate a warning signal.
[0055] In an embodiment, the generated warning signal can be transmitted
to one or more mobile computing devices by one or more communication units
114.The warning signal can pertain information of size and type of leakage, along
with location of leakage in the pipeline. The one or more mobile computing devices
can be a smartphone, a laptop, a tablet, a PDA, a desktop, and the likes. Upon
receiving the warning signal the associated person i.e. onsite engineer, member of
control room of the pipeline, or any other authorised person can ready and send a
team to repair the leakage instantly, thus reduce the chances of causalities.
[0056] In an embodiment, upon detection of the flammable leakage, the
signal generation unit 218 can generate alert signals. The alert signals can be
transmitted to at least one alert unit 112 positioned in the area where the flammable
leakage detected. Upon receiving the alert signals the alert unit 112 can produce
acoustic signal to notify nearby people to leave the area, or to take require action.
Moreover, the alert unit 112 can include but not limited to LED, buzzer, and/or
combination thereof. In a way of example and not as a limitation the buzzer can
produce sound, and the nearby people be notified to leave the area.
[0057] FIG. 3 illustrates an exemplary method in order to explain its
working, in accordance with an exemplary embodiment of the present disclosure.
[0058] As illustrated, an exemplary method (300) for monitoring leakage in
a pipeline is disclosed. At step (302), the method (300) can include acquiring one or more images of a pre-defined area of the pipeline, and the one or more images can be collected by the plurality of image acquisition units.
[0059] At step (304), the method (300) can include extracting and
processing, leakage-related data from the one or more images by a control unit 110. The leakage-related data can include pressure, temperature, corrosion, and stress inside the pipeline.

[0060] At step (306), the method (300) can include classifying, the leakage-
related data to determine size of the leakage in the pipeline.
[0061] At step (308), receiving location information of the associated image
acquisition unit upon detection of the leakage in the pipeline, where the location
information is received a location identifier 108 positioned in the area.
[0062] At step (310), transmitting a warning signal pertaining to size of the
leakage and location information of the leakage to one or more mobile computing devices by one or more communication units 114 to notify concerned authorities to take required action.
[0063] The foregoing discussion discloses and describes merely exemplary
embodiments of the present disclosure. As will be understood by those skilled in the art, the present disclosure may be embodied in other specific forms without departing from the spirit or essential characteristics thereof. Accordingly, the present disclosure is intended to be illustrative and not limiting thereof. The disclosure, including any readily discernible variants of the teachings herein, defines in part, the scope of the foregoing claim terminology.
ADVANTAGES OF THE PRESENT INVENTION
[0064] The present invention provides a system that assists in monitoring
leakage in pipelines.
[0065] The present invention provides a system to detect leaks over a
greater portion of a pipeline.
[0066] The present invention provides a system for leakage detection, that
is easy to install or use, and do not require special (e.g., pipeline modelling) skill to
use, install, or implement, detect smaller leaks, and avoid false positives.
[0067] The present invention provides a system to notify nearby people in
case of flammable leakage and reduce causalities.

[0068] The present invention provides a system to notify onsite
engineer/concerned person available at the location of leakage, or main control
room.
[0069] The present invention provides a system that reduce cost of
monitoring and maintenance.

We Claim:

1. A leakage detection system (100) for pipeline, the system comprising;
a plurality of image acquisition units 102 positioned along a length of pipeline transporting a fluid, wherein each of the plurality of image acquisition units configured to acquire one or more images of a pre-defined area of the pipeline, and storing the acquired one or more images in a first dataset;
a plurality of location identifiers 108 configured to acquired location information of each of the plurality of image acquisition units;
a control unit 110 operatively coupled to the first dataset and the plurality of location identifier, the control unit configured to:
receive the one or more images from a first dataset;
extract leakage-related data from the received one or more images using one or more learning techniques;
receive location information of the associated image acquisition unit from the associated location identifier, upon detection of leakage-related data in the pipeline;
classify the extracted leakage-related data to determine type and size ofthe leakage; and
generating a warning signal pertaining to size of the leakage and location information of the leakage, wherein the generated warning signal is transmitted to one or more mobile computing devices.
2. The leakage detection system (100) for pipeline as claimed in claim 1, wherein each of the image acquisition unit 102 comprises an image capturing unit 104 and an image processing unit 106, wherein the image processing unit include a visual geometry group (VGG) to process the one or more images by performing image classification and feature extraction.
3. The leakage detection system (100) for pipeline as claimed in claim 1, the leakage-related data includes pressure, temperature, corrosion, and stress inside the pipeline.

4. The leakage detection system (100) for pipeline as claimed in claim 1, wherein the control unit 110 is configured to transmit an alert signal to at least one alert unit positioned in an area where flammable type leakage detected in the pipeline.
5. The leakage detection system (100) for pipeline as claimed in claim 1, one or more communication units 114 configured to establish communication in between the plurality of image acquisition units, the plurality of location identifier, and the one or more mobile computing devices, wherein the one or more communication units include any or a combination of GSM module, Wireless Fidelity (Wi-Fi) Module, Wireless Local Area Network (WLAN), Bluetooth, Li-Fi Module and Zigbee.
6. The leakage detection system (100) for pipeline as claimed in claim 1, wherein the pipeline comprises any or a combination of underground pipeline, and the above-ground pipeline.
7. The leakage detection system (100) for pipeline as claimed in claim 1, wherein the pipeline transporting the fluid gas, oil, water, or combination thereof.
8. A method 300 for monitoring a pipeline,
Acquiring 302, one or more images of a pre-defined area of the pipeline, by a plurality of image acquisition units;
extracting and processing 304, leakage-related data from the one or more images, by a control unit;
classifying 306, the leakage-related data to determine size of the leakage;
receiving 308, location information of the associated image acquisition unit upon detection of the leakage in the pipeline; and
transmitting 310, a warning signal pertaining to size and type of the leakage and location information of the leakage to one or more mobile computing devices, by one or more communication units.
9. The method of claim 8, wherein the leakage-related data includes pressure,
temperature, corrosion, and stress inside the pipeline.

10. The method of claim 8, wherein upon detection of flammable leakage from the pipeline, at least one alert unit positioned in the area actuated to produce acoustic signal.