Embedded Damage Detection in Water Pipelines Using Wireless Sensor Networks

Mustafa, Hadil; Chou, Pai H.

doi:10.1109/hpcc.2012.230

Cited by 21 publications

(9 citation statements)

References 10 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…We have two vibration sensors, as described previously, one of which is an HE-HP vibration sensor and consumes more energy, with the other being an LE-LP vibration sensor and hence consuming less energy. These are used in an adaptive thresholding scheme [19,20] which was previously used to detect bursts in pipelines. A hierarchical scheme is used in which low-energy sensors are used for extended time periods to detect leaks and then wake up the HE-HP vibration sensor for event confirmation.…”

Section: Adaptive Sampling Algorithmmentioning

confidence: 99%

A novel multi-scale adaptive sampling-based approach for energy saving in leak detection for WSN-based water pipelines

Saqib

Mysorewala

Cheded

2017

Meas. Sci. Technol.

View full text Add to dashboard Cite

In this paper, we propose a novel monitoring strategy for a wireless sensor networks (WSNs)-based water pipeline network. Our strategy uses a multi-pronged approach to reduce energy consumption based on the use of two types of vibration sensors and pressure sensors, all having different energy levels, and a hierarchical adaptive sampling mechanism to determine the sampling frequency. The sampling rate of the sensors is adjusted according to the bandwidth of the vibration signal being monitored by using a wavelet-based adaptive thresholding scheme that calculates the new sampling frequency for the following cycle. In this multimodal sensing scheme, the duty-cycling approach is used for all sensors to reduce the sampling instances, such that the high-energy, high-precision (HE-HP) vibration sensors have low duty cycles, and the low-energy, low-precision (LE-LP) vibration sensors have high duty cycles. The low duty-cycling (HE-HP) vibration sensor adjusts the sampling frequency of the high duty-cycling (LE-LP) vibration sensor. The simulated test bed considered here consists of a water pipeline network which uses pressure and vibration sensors, with the latter having different energy consumptions and precision levels, at various locations in the network. This is all the more useful for energy conservation for extended monitoring. It is shown that by using the novel features of our proposed scheme, a significant reduction in energy consumption is achieved and the leak is effectively detected by the sensor node that is closest to it. Finally, both the total energy consumed by monitoring as well as the time to detect the leak by a WSN node are computed, and show the superiority of our proposed hierarchical adaptive sampling algorithm over a non-adaptive sampling approach.

show abstract

Section: Adaptive Sampling Algorithmmentioning

confidence: 99%

A novel multi-scale adaptive sampling-based approach for energy saving in leak detection for WSN-based water pipelines

Saqib

Mysorewala

Cheded

2017

Meas. Sci. Technol.

View full text Add to dashboard Cite

show abstract

“…However, it faces some challenges such as reliable long-range communication, precise time synchronization, power management and effective bandwidth usage [ 15 ]. The PipeTECT system was further improved by adding new modules at the sensing and data aggregation unit which reduced the total energy consumption significantly [ 16 ].…”

Section: Related Workmentioning

confidence: 99%

A Proposed Scalable Design and Simulation of Wireless Sensor Network-Based Long-Distance Water Pipeline Leakage Monitoring System

Almazyad

Seddiq

Alotaibi

et al. 2014

Sensors

View full text Add to dashboard Cite

Anomalies such as leakage and bursts in water pipelines have severe consequences for the environment and the economy. To ensure the reliability of water pipelines, they must be monitored effectively. Wireless Sensor Networks (WSNs) have emerged as an effective technology for monitoring critical infrastructure such as water, oil and gas pipelines. In this paper, we present a scalable design and simulation of a water pipeline leakage monitoring system using Radio Frequency IDentification (RFID) and WSN technology. The proposed design targets long-distance aboveground water pipelines that have special considerations for maintenance, energy consumption and cost. The design is based on deploying a group of mobile wireless sensor nodes inside the pipeline and allowing them to work cooperatively according to a prescheduled order. Under this mechanism, only one node is active at a time, while the other nodes are sleeping. The node whose turn is next wakes up according to one of three wakeup techniques: location-based, time-based and interrupt-driven. In this paper, mathematical models are derived for each technique to estimate the corresponding energy consumption and memory size requirements. The proposed equations are analyzed and the results are validated using simulation.

show abstract

“…The need to address this issue has led to a new body of knowledge-optimal sensor placement problem. The techniques of optimal sensor placement can be compared to the principle of leakage detection and pressure control valves management placement [13]- [15]. As a matter of fact, different methodologies have been proposed to address the succeeding issue of the optimal sensor placement [6]- [11].…”

Section: Introductionmentioning

confidence: 99%

Development of an Algorithm for the Estimation of Contamination Sources in a Water Distribution Network

et al. 2020

View full text Add to dashboard Cite

The complexity of a water distribution network (WDN) allows human imposition where accidental or intentional attack is possible. These attacks sometimes result in the contamination of water that has been treated at the treatment plant, and can eventually, be consumed by the society. However, the use of contaminated water has gross negative public health and socioeconomic implications on the society. Technically, being able to identify the source of contamination is particularly important for decision makers, so as to take immediate control strategies in order to minimize the consequences that can ensue from the use of contaminated water. There are two types of WDN analysis problem, which are: the steady state and the transient state conditions. In order to detect the continuous contamination that may be present in a WDN, this study considered a steady state condition. In this work, an approach for estimating the sources of contamination and the magnitude of concentration of the contaminant is proposed. Given a set of measurements, and by applying superposition technique, a model that embeds and relates the contaminant distribution to a set of given measurement in order to estimate the sources of contamination is formulated and, algorithm for solving it, is developed. The application of the proposed model is demonstrated on a water network with multiple injection contamination sources. The results of the estimated corresponding coefficient of determination for three cases are estimated (Case 1: 0.99894, Case 2: 0.99937 and Case 3 is 0.99974) while the corresponding root mean square were also obtained (Case 1: 0.000364, Case 2: 0.000351, Case 3: 0.000299) for a noise level of (5%). The same parameters were also obtained at a noise level of (10%). The obtained results verified the feasibility of the proposed novel approach, which can be applied to a larger water distribution network.

show abstract

Embedded Damage Detection in Water Pipelines Using Wireless Sensor Networks

Cited by 21 publications

References 10 publications

A novel multi-scale adaptive sampling-based approach for energy saving in leak detection for WSN-based water pipelines

A novel multi-scale adaptive sampling-based approach for energy saving in leak detection for WSN-based water pipelines

A Proposed Scalable Design and Simulation of Wireless Sensor Network-Based Long-Distance Water Pipeline Leakage Monitoring System

Development of an Algorithm for the Estimation of Contamination Sources in a Water Distribution Network

Contact Info

Product

Resources

About