Bio: Thailammai Chithambaram is an academic researcher from Indian Institute of Technology Madras. The author has contributed to research in topics: Wireless sensor network & Structural health monitoring. The author has an hindex of 2, co-authored 3 publications receiving 13 citations.
TL;DR: Process of deploying wireless sensor network in offshore structures for structural health monitoring is presented in this paper and compares the structural responses of offshore tension leg platform under different postulated failure cases through experimental investigations on scaled model.
Abstract: Process of deploying wireless sensor network in offshore structures for structural health monitoring is presented in this paper. Offshore structures are subjected to environmental loads with high uncertainties that are capable of causing damage during their service life. Preventive measures to safeguard the offshore platforms from such damages are not only innovative but also inevitable. Structural damages can be readily identified by monitoring their response behavior deploying dense array of sensors. Deploying wireless structural health monitoring (SHM) system ensures reduced installation time, compact design and cost reduction in comparison to that of the traditional wired systems. Wireless sensor network architecture for monitoring offshore platforms, proposed in the present study will acquire data using network of sensor nodes and transmits to the base station for post-processing. Present study compares the structural responses of offshore tension leg platform under different postulated failure cases through experimental investigations on scaled model. Acquired data are also hosted in the webpage after analyzing and post-processing. The alert monitoring system, which is an integral part of SHM triggers alert messages is an indigenous design.
04 Nov 2015-World Academy of Science, Engineering and Technology, International Journal of Environmental and Ecological Engineering
TL;DR: This paper presents the results of wireless sensor network based Structural Health Monitoring method applied to a scaled experimental model of offshore structure that underwent wave loading and determines the serviceability of the offshore structure which is subjected to various environment loads.
Abstract: The early-stage damage detection in offshore structures requires continuous structural health monitoring and for the large area the position of sensors will also plays an important role in the efficient damage detection. Determining the dynamic behavior of offshore structures requires dense deployment of sensors. The wired Structural Health Monitoring (SHM) systems are highly expensive and always needs larger installation space to deploy. Wireless sensor networks can enhance the SHM system by deployment of scalable sensor network, which consumes lesser space. This paper presents the results of wireless sensor network based Structural Health Monitoring method applied to a scaled experimental model of offshore structure that underwent wave loading. This method determines the serviceability of the offshore structure which is subjected to various environment loads. Wired and wireless sensors were installed in the model and the response of the scaled BLSRP model under wave loading was recorded. The wireless system discussed in this study is the Raspberry pi board with Arm V6 processor which is programmed to transmit the data acquired by the sensor to the server using Wi-Fi adapter, the data is then hosted in the webpage. The data acquired from the wireless and wired SHM systems were compared and the design of the wireless system is verified. Keywords—Condition assessment, damage detection, structural health monitoring, structural response, wireless sensor network.
TL;DR: This study concludes that implementation of structural health monitoring (SHM) to offshore platforms ensures safe operability and structural integrity, and proposes a novel scheme of deploying wireless sensor network for this purpose.
Abstract: Offshore platforms are of high strategic importance, whose preventive maintenance is on top priority. Buoyant Leg Storage and Regasification Platforms (BLSRP) are special of its kind as they handle LNG storage and processing, which are highly hazardous. Implementation of structural health monitoring (SHM) to offshore platforms ensures safe operability and structural integrity. Prospective damages on the offshore platforms under rare events can be readily identified by deploying dense array of sensors. A novel scheme of deploying wireless sensor network is experimentally investigated on an offshore BLSRP, including postulated failure modes that arise from tether failure. Response of the scaled model under wave loads is acquired by both wired and wireless sensors to validate the proposed scheme. Proposed wireless sensor network is used to trigger alert monitoring to communicate the unwarranted response of the deck and buoyant legs under the postulated failure modes. SHM triggers the alert mechanisms on exceedance of the measured data with that of the preset threshold values; alert mechanisms used in the present study include email alert and message pop-up to the validated user accounts. Presented study is a prima facie of SHM application to offshore platforms, successfully demonstrated in lab scale.
TL;DR: A complete evaluation of the MEMS accelerometers was performed by measuring amplitudes and frequencies of oscillations and comparing their dynamic characteristics with other accelerometers with higher precision to propose these sensors for measuring mechanical vibrations.
Abstract: In this paper, the use of MEMS accelerometers for measuring mechanical vibrations is presented. Also a wide review of the literature is performed by presenting the uses of the MEMS accelerometers in a great number of applications. These sensors are known for their low prices, low power consumption and low sizes, which enhance their use in applications such as energy harvesters, monitoring processes and for educational purposes. In order to propose these sensors for measuring vibrations, a complete evaluation of the MEMS accelerometers was performed by measuring amplitudes and frequencies of oscillations and comparing their dynamic characteristics with other accelerometers with higher precision. Moreover, two experiments were conducted: In the first one, the measurements of the amplitude given by a MEMS and a standard accelerometer while being excited with sinusoidal waves with different frequencies using a vibration exciter were taken and compared. For the second experiment, three MEMS sensors and a piezoelectric accelerometer were used to measure the accelerations of a 3-DOF shear-building excited by an unbalanced DC motor. The signals obtained were compared in the time and frequency domains; for the last case, the wavelet transform, the wavelet coherence and the power spectrum density were used.
TL;DR: In this work, contributions of uncertainty of a calibration procedure by comparison for digital MEMS accelerometers at high frequency are investigated in order to provide traceability to primary standard.
Abstract: Advanced manufacturing applications often involve the use of vibration control systems for both process control and defect prevention. Recently, the use of networks of low-cost digital MEMS accelerometer has become a widespread practice, being an economically competitive and promising way to improve quality and productivity effectiveness. Nevertheless, due to the lack of metrological traceability, these devices are currently not reliable to quantify amplitude and frequency of the actual vibrational motion. In this work, contributions of uncertainty of a calibration procedure by comparison for digital MEMS accelerometers at high frequency are investigated in order to provide traceability to primary standard.
TL;DR: An Internet of Things vibration sensing system has been developed to provide a promising alternative to the traditional vibration monitoring system and has been successfully validated by a series of tests in the laboratory and on a selected construction site.
Abstract: Construction activities often generate intensive ground-borne vibrations that may adversely affect structure safety, human comfort, and equipment functionality. Vibration monitoring systems are commonly deployed to assess the vibration impact on the surrounding environment during the construction period. However, traditional vibration monitoring systems are associated with limitations such as expensive devices, difficult installation, complex operation, etc. Few of these monitoring systems have integrated functions such as in situ data processing and remote data transmission and access. By leveraging the recent advances in information technology, an Internet of Things (IoT) sensing system has been developed to provide a promising alternative to the traditional vibration monitoring system. A microcomputer (Raspberry Pi) and a microelectromechanical systems (MEMS) accelerometer are adopted to minimize the system cost and size. A USB internet dongle is used to provide 4G communication with cloud. Time synchronization and different operation modes have been designed to achieve energy efficiency. The whole system is powered by a rechargeable solar battery, which completely avoids cabling work on construction sites. Various alarm functions, MySQL database for measurement data storage, and webpage-based user interface are built on a public cloud platform. The architecture of the IoT vibration sensing system and its working mechanism are introduced in detail. The performance of the developed IoT vibration sensing system has been successfully validated by a series of tests in the laboratory and on a selected construction site.
TL;DR: In this article , a highly stretchable rope-like triboelectric nanogenerator (R-TENG) is proposed and investigated to monitor the mechanical loads of marine structures.
Abstract: Real-time monitoring in marine structures is vital to prevent maritime accidents. In this study, a highly-stretchable rope-like triboelectric nanogenerator (R-TENG) is proposed and investigated to monitor the mechanical loads of marine structures. The designed R-TENG is composed of outer latex tube and inner silicone rubber core. A series of experiments reveal that the voltage output of the R-TENG increases linearly with the strain in the elastic region of 140%. In addition, the R-TENG can also respond well to other mechanical stimuli such as bending and pressing. More importantly, the electrical output of the R-TENG can remain almost constant even under 93% humidity atmosphere. Finally, the R-TENG has been successfully demonstrated in monitoring the typical mechanical loads in marine structures, including stretching, colliding and bending. Therefore, this R-TENG can be utilized as an alternative sensor to realize the self-powered monitoring in marine structures.