WSNs based Oil Well Health Monitoring and Control Using ARM9 Processor

The existing oil pumping system is a high power consuming process and has incapabilitys of CPUs structural health monitoring. Due to the environmental conditions and remote locations of oil and gas sites, it is expensive to physically visit assets for maintenance and repair. As the demand for oil and gas increases, reducing operating and maintenance costs and increasing reliability, this paper develops a sensor network based monitoring and control system, and improves the level of oil field security, enhance the security checking, and strengthen the management of digitalization and information. The system mainly consists of various sensors like temperature sensor, voltage sensor, current sensor, level sensor, PH sensor and gas sensor. Here we use gas sensor to detect the flammable gas which generally evolves from the oil wells. If any such detection occurs, automatically exhaust fan will switch on to pass away the particles. As like, in case if temperature level is high, cooling fan will trigger to reduce or maintain the particular temperature in the wells. With the help of current and potential transformer we can find out the fluctuations in the pumping section. If the level of oil varies from the indicated level it gives an alert message via voice recorder. To measure the level of humidity, we use PH sensor. All the sensors data is transmitted and monitored in PC using ARM processor. Also we can communicate this sensor data to other PCs using Zigbee technology.

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A Blockchain-Enabled Approach for Online Stream Sensor Data Protection in Cyber-Physical Manufacturing Systems

10.1115/detc2021-72023 ◽

2021 ◽

Author(s):

Zhangyue Shi ◽

Chenang Liu ◽

Chen Kan ◽

Wenmeng Tian ◽

Yang Chen

Keyword(s):

Information Technologies ◽

Manufacturing Systems ◽

Rapid Development ◽

Data Access ◽

Sensor Data ◽

False Alarms ◽

Monitoring And Control ◽

Stream Data ◽

Physical Security ◽

And Control

Abstract With the rapid development of the Internet of Things and information technologies, more and more manufacturing systems become cyber-enabled, which significantly improves the flexibility and productivity of manufacturing. Furthermore, a large variety of online sensors are also commonly incorporated in the manufacturing systems for online quality monitoring and control. However, the cyber-enabled environment may pose the collected online stream sensor data under high risks of cyber-physical attacks as well. Specifically, cyber-physical attacks could occur during the manufacturing process to maliciously tamper the sensor data, which could result in false alarms or failures of anomaly detection. In addition, the cyber-physical attacks may also illegally access the collected data without authorization and cause leakage of key information. Therefore, it becomes critical to develop an effective approach to protect online stream data from these attacks so that the cyber-physical security of the manufacturing systems could be assured. To achieve this goal, an integrative blockchain-enabled method, is proposed by leveraging both asymmetry encryption and camouflage techniques. A real-world case study that protects cyber-physical security of collected stream data in additive manufacturing is provided to demonstrate the effectiveness of the proposed method. The results demonstrate that malicious tampering could be detected in a relatively short time and the risk of unauthorized data access is significantly reduced as well.

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AUTOMATED WIRELESS STRUCTURAL HEALTH MONITORING AND CONTROL USING TUNED LIQUID COLUMN DAMPERS

Proceedings of the 7th International Conference on Computational Methods in Structural Dynamics and Earthquake Engineering (COMPDYN 2015) ◽

10.7712/120119.6911.18771 ◽

2019 ◽

Author(s):

Kosmas Dragos ◽

George Manolis ◽

Kay Smarsly

Keyword(s):

Structural Health Monitoring ◽

Health Monitoring ◽

Liquid Column ◽

Monitoring And Control ◽

Structural Health ◽

Liquid Column Dampers ◽

And Control

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Arduino based gas leakage and temperature monitoring and control system

International Journal of Informatics and Communication Technology (IJ-ICT) ◽

10.11591/ijict.v9i3.pp171-178 ◽

2020 ◽

Vol 9 (3) ◽

pp. 171

Author(s):

Adoyi Boniface ◽

A.Y. Nasir ◽

A. M. Hassan

Keyword(s):

Gas Sensor ◽

Leakage Detection ◽

Liquefied Petroleum Gas ◽

Monitoring And Control ◽

Compressed Natural Gas ◽

Monitoring And Control System ◽

Gas Leakage ◽

Industrial Sectors ◽

And Control ◽

Preventive Methods

<span lang="EN-US">Gas leakage is a major problem with industrial sectors, residential premises and gas powered vehicles like CNG (Compressed Natural Gas) buses etc. One of the preventive methods to stop accidents associated with the gas leakage is to install a gas leakage detection device at vulnerable places. The aim of this project is to develop such a device that can automatically detect and control gas leakages and also monitor temperature in vulnerable areas. The system detects the leakage of the LPG (Liquefied Petroleum Gas) using a gas sensor and then also monitors the temperature using a temperature sensor. When the LPG concentration in the air exceeds a certain level, the gas sensor senses the gas leakage and the output of the sensor goes LOW, the system then opens the exit windows, and then uses the GSM to alert the person about the gas leakage via SMS. Also, when the temperature of the environment exceeds a certain limit, it then turns ON the LED (indicator) and make an alarm through the buzzer. An LCD (16x2) displays the current temperature and gas leakage status in degree Celsius and PPM respectively.</span>

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Applications of Machine Learning in Process Monitoring and Controls of L-PBF Additive Manufacturing: A Review

Applied Sciences ◽

10.3390/app112411910 ◽

2021 ◽

Vol 11 (24) ◽

pp. 11910

Author(s):

Dalia Mahmoud ◽

Marcin Magolon ◽

Jan Boer ◽

M.A Elbestawi ◽

Mohammad Ghayoomi Mohammadi

Keyword(s):

Machine Learning ◽

Defect Detection ◽

In Situ Monitoring ◽

Sensor Data ◽

Learning Approaches ◽

Monitoring And Control ◽

In Situ Sensors ◽

Applications Of Machine Learning ◽

And Control

One of the main issues hindering the adoption of parts produced using laser powder bed fusion (L-PBF) in safety-critical applications is the inconsistencies in quality levels. Furthermore, the complicated nature of the L-PBF process makes optimizing process parameters to reduce these defects experimentally challenging and computationally expensive. To address this issue, sensor-based monitoring of the L-PBF process has gained increasing attention in recent years. Moreover, integrating machine learning (ML) techniques to analyze the collected sensor data has significantly improved the defect detection process aiming to apply online control. This article provides a comprehensive review of the latest applications of ML for in situ monitoring and control of the L-PBF process. First, the main L-PBF process signatures are described, and the suitable sensor and specifications that can monitor each signature are reviewed. Next, the most common ML learning approaches and algorithms employed in L-PBFs are summarized. Then, an extensive comparison of the different ML algorithms used for defect detection in the L-PBF process is presented. The article then describes the ultimate goal of applying ML algorithms for in situ sensors, which is closing the loop and taking online corrective actions. Finally, some current challenges and ideas for future work are also described to provide a perspective on the future directions for research dealing with using ML applications for defect detection and control for the L-PBF processes.

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A Wireless Gas Sensor Network to Monitor Indoor Environmental Quality in Schools

Sensors ◽

10.3390/s18124345 ◽

2018 ◽

Vol 18 (12) ◽

pp. 4345 ◽

Cited By ~ 11

Author(s):

Alvaro Ortiz Perez ◽

Benedikt Bierer ◽

Louisa Scholz ◽

Jürgen Wöllenstein ◽

Stefan Palzer

Keyword(s):

Sensor Network ◽

Gas Sensor ◽

Environmental Quality ◽

Energy Savings ◽

Environmental Parameters ◽

Well Being ◽

Sensor Nodes ◽

Indoor Environmental Quality ◽

Monitoring And Control ◽

And Control

Schools are amongst the most densely occupied indoor areas and at the same time children and young adults are the most vulnerable group with respect to adverse health effects as a result of poor environmental conditions. Health, performance and well-being of pupils crucially depend on indoor environmental quality (IEQ) of which air quality and thermal comfort are central pillars. This makes the monitoring and control of environmental parameters in classes important. At the same time most school buildings do neither feature automated, intelligent heating, ventilation, and air conditioning (HVAC) systems nor suitable IEQ monitoring systems. In this contribution, we therefore investigate the capabilities of a novel wireless gas sensor network to determine carbon dioxide concentrations, along with temperature and humidity. The use of a photoacoustic detector enables the construction of long-term stable, miniaturized, LED-based non-dispersive infrared absorption spectrometers without the use of a reference channel. The data of the sensor nodes is transmitted via a Z-Wave protocol to a central gateway, which in turn sends the data to a web-based platform for online analysis. The results show that it is difficult to maintain adequate IEQ levels in class rooms even when ventilating frequently and that individual monitoring and control of rooms is necessary to combine energy savings and good IEQ.

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Enhancing the Resiliency of Smart Grid Monitoring and Control

Encyclopedia of Information Science and Technology, Fourth Edition ◽

10.4018/978-1-5225-2255-3.ch267 ◽

2018 ◽

pp. 3056-3065

Author(s):

Wenbing Zhao

Keyword(s):

Fault Tolerance ◽

Electric Power ◽

Health Monitoring ◽

Power Grid ◽

Byzantine Fault Tolerance ◽

Monitoring And Control ◽

Byzantine Fault ◽

Electric Power Grid ◽

Grid Monitoring ◽

And Control

In this chapter, we present the justification and a feasibility study of applying the Byzantine fault tolerance (BFT) technology to electric power grid health monitoring. We propose a set of BFT mechanisms needed to handle the PMU data reporting and control commands issuing to the IEDs. We report an empirical study to assess the feasibility of using the BFT technology for reliable and secure electric power grid health monitoring and control. We show that under the LAN environment, the overhead and jitter introduced by the BFT mechanisms are negligible, and consequently, Byzantine fault tolerance could readily be used to improve the security and reliability of electric power grid monitoring and control while meeting the stringent real-time communication requirement for SCADA operations.

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Combining Health Monitoring and Control

Diagnostics and Prognostics of Engineering Systems ◽

10.4018/978-1-4666-2095-7.ch012 ◽

2013 ◽

pp. 230-255

Author(s):

Teresa Escobet ◽

Joseba Quevedo ◽

Vicenç Puig ◽

Fatiha Nejjari

Keyword(s):

Health Monitoring ◽

Fault Tolerant ◽

Operating Conditions ◽

Monitoring And Control ◽

New Paradigm ◽

System Health Monitoring ◽

On Line ◽

And Control ◽

System Characteristics ◽

Feature System

This chapter proposes the combination of system health monitoring with control and prognosis creating a new paradigm, the health-aware control (HAC) of systems. In this paradigm, the information provided by the prognosis module about the component system health should allow the modification of the controller such that the control objectives will consider the system’s health. In this way, the control actions will be generated to fulfill the control objectives, and, at the same time, to extend the life of the system components. HAC control, contrarily to fault-tolerant control (FTC), adjusts the controller even when the system is still in a non-faulty situation. The prognosis module, with the main feature system characteristics provided by condition monitoring, will estimate on-line the component aging for the specific operating conditions. In the non-faulty situation, the control efforts are distributed to the system based on the proposed health indicator. An example is used throughout the chapter to illustrate the ideas and concepts introduced.

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Mechanical Design and Analysis of an Intelligent Oil Well Sensory System

ASME 2010 10th Biennial Conference on Engineering Systems Design and Analysis, Volume 2 ◽

10.1115/esda2010-24713 ◽

2010 ◽

Author(s):

Atefeh Salmasi ◽

Aghil Yousefi-Koma ◽

Mohammad Hossein Soorgee

Keyword(s):

Oil And Gas ◽

Mechanical Design ◽

Sensory System ◽

High Price ◽

Oil Well ◽

Gas Industry ◽

Oil And Gas Fields ◽

Sensing Technology ◽

And Control ◽

Measurement And Control

Optimal revenue of oil and gas fields is of interest due to high price and limited amount of these sources of energy. In this way, smart well technology provides a numerous range of benefits and for these great advantageous is widely used in oil/gas industry. This technology involves down-hole measurement and control of well bore and reservoir flow. One of the most important down-hole control subsystems in a smart well is pressure and temperature sensing system which can help the reservoir being modeled accurately. The purpose of this paper is to design and analysis a new sensory package for a desired oil well. A brief review of the advantages of fiber optic sensing technology in smart well control system is performed. Having studied several possibilities of installation systems for sensors, a new arrangement and casing for temperature/pressure sensor is developed here. Effect of pressure and temperature on stress distribution in the casing has been investigated and a suitable casing is obtained.

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