South Asian Journal of Engineering and Technology Vol.4, No.1 (2018) 43–51

ISSN No: 2454-9614

StudyofIsolated Pipeline in Petroleum industries Using IoTS. Kesavan M.E., AP/S. Aiswarya M.E., AP

C.R.Tamizhanambi.M.S.,, AP/M.Parthiban, M.E.,

Electronics and Instrumentation Engineering,

Mahendra Engineering College,Nammakal, Tamilnadu, India

*Corresponding AuthorS. Kesavan M.E

E-mail: mrsrik7@gmail.com

Received: 24/1/2018, Revised: 18/2/2018 and Accepted: 1/4/2018

Abstract

Identification and localization of anomalies in pipeline structure is an essential requirement in many industries. There are numerous reasons that can lead to pipeline damage and impairment. In chemical and petroleum industry this damage is directly connected to the safety of assets as well as humans. Hence, continuous monitoring and timely response is expected. This paper provides an insight into different leakage problems that may arise in various pipeline industries. Wireless Sensor Network (WSN) solutions that may be applied to these problems are deliberated and evaluated. Based on this comparison recommendations and solutions are specified.Keywords: Pipeline, Wireless Sensor Network (WSN, Ultrasonic Senor, Moisture Sensor, IoT, PIC.

1. Introduction

Pipelines are the primary mean to transport various goods from one point to another. Liquids, gases, chemicals, oils, bio fuels and many other important assets of a county are usually shipped using pipelines. Water pipelines are one of the most vital structure for transporting water for drinking or irrigation over long distances. This transportation can be from over hills, canals or other cities [1]. This long distance transportation must be carefully and remotely monitored against security threats, pollution problem, environmental impact and leakage loss. Oil and gas pipelines are made from steel or plastic which are usually buried under the soil or exposed to temperature pressure loads. Some of the pipelines are operated at high pressure and temperature, which can often result in pipelines breakdown, causing severe damage to humans and unwanted interruption of oil, gas or water supplies. Hence there is a need for active and remote monitoring system for these pipelines. However, the system should remain scalable and cost effective. Pipeline inspection and repair presents a number of challenges that are quite unique. Pipelines extensive deployment, high cost, high risk and often hard to access conditions require uninterrupted monitoring as well as an optimization of maintenance interventions. Active monitoring is an expensive process using traditional maintenance systems, especially in a hazardous environment and elevated temperature and pressure load. It is also a time-intensive procedure that involves workers covering large areas by vehicle to physically examine and repair them as needed. Remote monitoring is the latest trend for pipeline monitoring. Different architectures are proposed and deployed for reliable and long term monitoring of aging, corrosion, leakages, cracks and physical damages from third parties. In Kingdom of Saudi Arabia hundreds of kilometers of underground pipelines are laid to connect the cities with the Arabian Gulf through the desert. Maintenance and monitoring of such large infrastructure is a challenging but essential task. Russia is a renowned exporter of crude oil. In 2007 Russia exported almost 1.3 million barrels of crude oil per day via underground pipelines. The oil traveled from Russia all the way to Ukraine, Germany, Poland, and other destinations in Europe [2] . Underground pipelines are considered as the safest way to

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transport liquids and gases far across the globe. However statistical observations have proved that large pipelines experience at least one harmful leakage every year. Junior, et al. [3] reported that pipeline leakage can cause economic loss, and environmental pollution problems. Risk of human injuries is also increased. Thus, the security and monitoring of pipeline infrastructure becomes a major challenge [4]. Some of the factors contributing to leaks are old and weak pipeline construction, poorly maintained valves and not enough corrosion protection [5]. Economic losses caused by leakage increases annually and cause accumulating losses [6]. Pipeline monitoring system can be wired, wireless or a combination of both to transfer data from pipelines to control station. Since pipeline networks are in line, connectivity always remains a critical feature. Pipeline inspection can be classified into three major categories • Using smart moveable sensors. • Using standalone monitoring system or device. • Using resident pipeline sensors. Smart movable sensing devices are robots, pigs, or crawlers. These are intelligent robotic devices that can move inside or above a pipeline to inspect the interior/exterior conditions. Standalone inspection systems utilize phased array ultrasonic technology. They are usually mounted on the outer surface of pipelines where they use the electromagnetic waves to detect corrosion and defects at Computing and Digital Systems (C-CODE) given point. Handheld devices are also used for manual operation at certain locations.

I. BLOCK DIAGRAM AND SYSTEM SPECIFICATIONS

HARDWARE SPECIFICATION i. PIC MICROCONTROLLER

ii. LCD DISPLAYiii. MOISTURE SENSORiv. ULTRASONIC SENSORv. GPRS

vi. SOFTWARE SPECIFICATIONvii. MP LAB---Controller Side

viii. JAVA---Mobile sidePIC Peripheral Interface Controller made by microchip technology. All the current models are using flash

memory for program and storage. The hardware capabilities of PIC range up to 144-pin SMD chips. The software tools supported were MPLAB X, assemblers and c/c++ compilers and programmers hardware MPLAB and PICK it series.The main advantage of CMOS and RISC combination is low power consumption resulting in a very small chip size with a small pin count. The main advantage of CMOS is that it has immunity to noise than other fabrication technique.

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Fig.1 Block Diagram of proposed system

Fig.2 Sensor based pipeline monitoring

Sensor based monitoring:Smart mobile sensing devices are the nodes which can easily move inside the pipeline along with the liquid [7].They are put inside the pipe from a source point and theykeep traveling until they reach the designated sink point.When the sensor reaches the sink the information stored inthe memory of sensor is copied to the backend system. Thisinformation includes the sensors readings, as well aslocation information taken by the node throughout its longtrip inside the pipeline. The node observation is subjected tooffline analysis to locate the leakage. The sensor nodes maylocate its location based on its signal exposure to the RadioFrequency Identification (RFID) tags that are placed outsidethe pipe on fixed places. The number of tags used isinversely proportional to the distance between the tags (Δd).

ULTRASONIC SENSOR

Fig.2 Ultrasonic Wavelength Configuration

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Fig.3 Ultrasonic Sensor Working Model

Ultrasonic sensor is a device used to measure the distance to an object by using sound waves. If a garbage bin has been filled day by day. The sender sends the waves to be travelled at the top of the garbage bin and the receiver receives the frequency of the waves at every time. If the time of reflection received is taken less time than the trash has been filled. The frequencies are higher frequency than the human audible range. The frequencies are typically 12 kHz or less, while some humans can hear frequencies up to 20 kHz. Ultrasonic waves consist of frequencies greater than 20 kHz and exist in excess of 25 MHz.

Fig.4 Ultrasonic wave detectionUltrasonic waves are used in many applications including plastic welding, medicine, jewelry cleaning, and

nondestructive test. Within nondestructive test, ultrasonic waves give us the ability to “see through” solid/opaque material and detect surface or internal flaws without affecting the material in an adverse manner.

II. SIMULATIONDynamic scheduling is aware of which certain full bins capacity levels are reached. Moreover, dynamic

scheduling enhances top queries with IOT real-time sensor and context information. The proposed dynamic scheduling model proved robust when compared with other static models studied in the literature.

Moisture sensorSoil moisture sensors measure the volumetric water content in soil. Since the direct gravimetric

measurement of free soil moisture requires removing, drying, and weighting of a sample, soil moisture sensors measure the volumetric water content indirectly by using some other property of the soil, such as electrical

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resistance, dielectric constant, or interaction with neutrons, as a proxy for the moisture content. The relation between the measured property and soil moisture must be calibrated and may vary depending on environmental factors such as soil type, temperature, or electric conductivity. Reflected microwave radiation is affected by the soil moisture and is used for remote sensing in hydrology and agriculture. Portable probe instruments can be used by farmers or gardeners.

Soil moisture sensors typically refer to sensors that estimate volumetric water content. Another class of sensors measure another property of moisture in soils called water potential; these sensors are usually referred to as soil water potential sensors and include tensiometers and gypsum blocks.

Fig 5. Moisture sensorOTHER SOFTWARE USED:

The last category of waste management context, i.e., software analytics, focuses on the following components: (i) the Decision Support System (DSS), which depicts the inference process to the stakeholders; (ii) the GIS, which focuses on the; (iii) the dynamic scheduling,; (iv) the dynamic routing, which involves real-time changes in the pre-defined route to better serve the needs of on-going waste management to any change in the context. The algorithms adopted in the software analytics part of the contextual aspect of waste management are strictly dynamic which means that the proposed waste collection systems are comprised of pure ICT functionality. This means that a set of intelligent algorithms are proposed to facilitate the whole process from the collection to the final disposal taking into consideration various types of information to increase the performance. In addition, the software analytics part involves the following features: (i) the architecture, (ii) the social context and (iii) the experimental data. The architecture of a waste management system is either defined explicitly or implied as a part of the overall system design. The social context best describes the dynamics and social impacts of waste management on citizens. The last feature of software analytics is the experimental data used for evaluation of the proposed approaches. Data incorporated are either synthetic, created in the laboratories, or real, collected from observations in the SCs.[2].

III. PROCEDURE FOR SIMULATION WORK

STEP 1: OPEN ISIS file and new design

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South Asian Journal of Engineering and Technology Vol.4, No.1 (2018) 43–51

STEP 2: SAVE the current file and select template size and now default used.

STEP 3: SAVE the untitled as your wish

STEP 3: TO select the components, click on the component symbol.

STEP 4: CLICK on the pick from libraries to search the different components.

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STEP 5: The selected components will appear in the devices list. Select the component and place it in the  design sheet by left-click.STEP 6: Double click on the component to edit the properties of the components and click on Ok.

STEP 7:After the connections made click on the play button.

I. RESULT AND DISCUSSION

Table 1: Result for tested abnormal conditionThe Above conditioned is tested for abnormal pipeline this refers according to the set value as it not matched so it is concluded that it should found the abnormalities on pipeline as mentioned in the remarks as concerned .

Table 2: Result for tested normal conditionThe Above conditioned is tested for normal pipeline this refers according to the set value as it not matched so it is

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concluded that it should found the abnormalities on pipeline as mentioned in the remarks as concernedII. CONCLUSION AND FUTURE WORK

Fluid leakage is a worldwide hassling matter that needs to be dealt with effectively; otherwise it will cause huge economic and raw materials losses. In this paper, we introduced four WSN technologies for detecting leaks. Ultrasonic sensor based WSN for underground pipeline leakage detection and localization was discussed. This solution provides low cost monitoring system and power consumption for underground wireless communications that seems to be effective due to its low attenuation. MI-based sensors can be utilized both inside and outside the pipes for better leakage detection.

REFERENCES[1] M. E. Stoica, L. Avram, I. Onutu, A. Barbulescu, C. Panaitescu, and T. Cristescu, "Time behaviour of hydrocarbon pollutants in soils polluted with oil and salt water," Revista de Chimie, vol. 67, pp. 357-361, 2016.

[2] Z. Sun, P. Wang, M. C. Vuran, M. A. Al-Rodhaan, A. M. AlDhelaan, and I. F. Akyildiz, "MISE-PIPE: Magnetic induction-based wireless sensor networks for underground pipeline monitoring," Ad Hoc Networks, vol. 9, pp. 218-227, 2011.

[3] C. A. V. Junior, J. L. De Medeiros, and O. D. Q. F. Araújo, "ARX modeling approach to leak detection and diagnosis," Journal of Loss Prevention in the Process Industries, vol. 23, pp. 462-475, 2010.

[4] A. Ostfeld, J. G. Uber, E. Salomons, J. W. Berry, W. E. Hart, C. A. Phillips, et al., "The battle of the water sensor networks (BWSN): A design challenge for engineers and algorithms," Journal of Water Resources Planning and Management, vol. 134, pp. 556-568, 2008.

[5] G. Oren and N. Stroh, "Antileaks: A device for detection and discontinuation of leakages in domestic water supply systems," European Journal for Young Scientist and Engineers, vol. 1, pp. 10- 13, 2012. [6] A. Lambert, "International report: water losses management andtechniques," Water Science and Technology: Water

Supply, vol. 2, pp. 1-20, 2002.

[6] A. Lambert, "International report: water losses management and techniques," Water Science and Technology: Water Supply, vol. 2, pp. 1-20, 2002.

[7] A. S. Almazyad, Y. M. Seddiq, A. M. Alotaibi, A. Y. Al-Nasheri,M. S. BenSaleh, A. M. Obeid , et al., "A proposed scalable designand simulation of wireless sensor network-based long-distancewater pipeline leakage monitoring system," Sensors, vol. 14, pp.3557-3577, 2014.

[8] X. Chen and P. Yu, "Research on hierarchical mobile wirelesssensor network architecture with mobile sensor nodes," inBiomedical Engineering and Informatics (BMEI), 2010 3rdInternational Conference on, 2010, pp. 2863-2867.

[9] J.-H. Kim, G. Sharma, N. Boudriga, and S. S. Iyengar, "SPAMMS:A sensor-based pipeline autonomous monitoring and maintenancesystem," COMSNETS, vol. 10, pp. 118-127, 2010.

[10] W. Gong, M. A. Suresh, L. Smith, A. Ostfeld, R. Stoleru, A.Rasekh, et al., "Mobile sensor networks for optimal leak andbackflow detection and localization in municipal water networks,"Environmental Modelling & Software,

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Sl.No. Sensor Tested

Output

Set value range of Sensor

Remark

1. Combined Moisture Sensor 1 & Moisture Sensor 2

30 >40 normal

2. Moisture Sensor 2 25 >40 normal

3. Ultrasonic sensor 35 <30 normal

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vol. 80, pp. 306-321, 2016.

[11] L. Perelman and A. Ostfeld, "Operation of remote mobile sensorsfor security of drinking water distribution systems," Water research,vol. 47, pp. 4217-4226, 2013.

[12] Z. Sun and I. F. Akyildiz, "Magnetic induction communications forwireless underground sensor networks," Antennas and Propagation,IEEE Transactions on, vol. 58, pp. 2426-2435, 2010.

[13] I. F. Akyildiz, P. Wang, and Z. Sun, "Realizing underwatercommunication through magnetic induction," CommunicationsMagazine, IEEE, vol. 53, pp. 42-48, 2015.

[14] X. Tan, Z. Sun, and I. F. Akyildiz, "Wireless Underground SensorNetworks: MI-based communication systems for undergroundapplications," IEEE Antennas and Propagation Magazine, vol. 57,pp. 74-87, 2015.

[15] Y. Lijian, L. Gang, Z. Guoguang, and G. Songwei, "Sensordevelopment and application on the oil-gas pipeline magnetic fluxleakage detection," in 2009 9th International Conference onElectronic Measurement&Instruments, 2009.

[16] H. Kikuchi, K. Sato, I. Shimizu, Y. Kamada, and S. Kobayashi,"Feasibility study of application of MFL to monitoring of wallthinning under reinforcing plates in nuclear power plants,"Magnetics, IEEE Transactions on, vol. 47, pp. 3963-3966, 2011.

[17] S. Bhadra, G. Bridges, and D. Thomson, "Coupled coil sensor fordetecting surface corrosion on steel reinforcement," in AntennaTechnology and Applied Electromagnetics & the AmericanElectromagnetics Conference (ANTEM-AMEREM), 2010 14thInternational Symposium on, 2010, pp. 1-4.

[18] E. Farjah, H. Givi, and T. Ghanbari, "Application of an efficientRogowski coil sensor for switch fault diagnosis and capacitor ESRmonitoring in non-isolated single switch DC-DC converters," 2016.

[19] M. Crescentini, A. Romani, and E. Sangiorgi, "Physical simulationsof response time in Hall sensor devices," in Ultimate Integration onSilicon (ULIS), 2014 15th International Conference on, 2014, pp.89-92.

[20] T. Chang and K.-C. Juang, "CMOS SC-spinning, current-feedbackHall sensor for high speed and low cost applications," in SENSORS,2014 IEEE, 2014, pp. 527-530.

[21] J. Wang, L. Min, H. Qi, and C. Wang, "An over-coupled fusedcoupler based acoustic emission sensor for detecting partialdischarges," in Photonics and Optoelectronics (SOPO), 2012Symposium on, 2012, pp. 1-4.

[22] M. Yifan, C. Xiwang, Y. Yong, M. Lin, and H. Xiaojuan, "Leakagedetection in a CO 2 pipeline using Acoustic emission techniques," inSignal Processing (ICSP), 2014 12th International Conference on,2014, pp. 78-82.

[23] J. Yoon and D. He, "Planetary gearbox fault diagnostic methodusing acoustic emission sensors," Science, Measurement &Technology, IET, vol. 9, pp. 936-944, 2015.

[24] S. Li, Y. Wen, P. Li, J. Yang, and L. Yang, "Leak detection andlocation for gas pipelines using acoustic emission sensors," inUltrasonics Symposium (IUS), 2012 IEEE International, 2012, pp.957-960.

[25] B. Yang, M. Li, Q. Li, and Y. Lu, "Ultrasonic monitoring system foroil and gas pipeline corrosion," in 2012 Fourth InternationalConference on Multimedia Information Networking and Security,2012, pp. 381-383.

[26] F. Li, Y. Liu, L. Wang, and Y. Chen, "Analysis of the couplingoptical fiber ultrasonic sensor for partial

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discharges detection," in2015 IEEE 11th International Conference on the Properties andApplications of Dielectric Materials (ICPADM), 2015, pp. 991-994.[27] Y. Wang and S. Li, "Non-destructive Testing of Pipeline LiquidsUsing Ultrasonic Technology," in Optoelectronics and ImageProcessing (ICOIP), 2010 International Conference on, 2010, pp.43-46.

BIOGRAPHY:S.KESAVAN, Assistant Professor, Electronics and Instrumentation Engineering in Mahendra Engineering College (Autonomous) under Anna University, Tamilnadu, India.

ARUN.M pursuing B.E - Electronics and Instrumentation Engineering in Mahendra Engineering College (Autonomous) under Anna University, Tamilnadu, India.

RIYAZUDEEN.M, pursuing B.E - Electronics and Instrumentation Engineering in Mahendra Engineering College (Autonomous) under Anna University, Tamilnadu, India.

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