Water Pipeline Leakage Detection Based on Machine Learning and Wireless Sensor Networks

The detection of water pipeline leakage is important to ensure that water supply networks can operate safely and conserve water resources. To address the lack of intelligent and the low efficiency of conventional leakage detection methods, this paper designs a leakage detection method based on machine learning and wireless sensor networks (WSNs). The system employs wireless sensors installed on pipelines to collect data and utilizes the 4G network to perform remote data transmission. A leakage triggered networking method is proposed to reduce the wireless sensor network’s energy consumption and prolong the system life cycle effectively. To enhance the precision and intelligence of leakage detection, we propose a leakage identification method that employs the intrinsic mode function, approximate entropy, and principal component analysis to construct a signal feature set and that uses a support vector machine (SVM) as a classifier to perform leakage detection. Simulation analysis and experimental results indicate that the proposed leakage identification method can effectively identify the water pipeline leakage and has lower energy consumption than the networking methods used in conventional wireless sensor networks

Small unmanned airborne systems to support oil and gas pipeline monitoring and mapping

Acknowledgments We thank Johan Havelaar, Aeryon Labs Inc., AeronVironment Inc. and Aeronautics Inc. for kindly permitting the use of materials in Fig. 1.Peer reviewedPublisher PD

Development of Ammonia Gas Leak Detection and Location Method

This paper proposed the gas for industrial ammonia leak diffusion model and the Gauss method of leakage localization. A set of wireless ammonia leak alarm system is composed of sensor node, network coordinator and host used in the industrial field was developed, the purpose is to reduce the loss of property caused by the leakage of ammonia industry. Using the monitoring system to carry out the ammonia leak location simulation measurement experiment, the result shows that the relative positioning error of the monitoring system is about 12%, which meets the needs of industrial production safety monitoring. Using the wireless sensor network to monitor the concentration of ammonia gas and locate the leakage source, it solves the problems of traditional wired alarm system, such as difficult wiring and weak expansibility, which helps to find the leak timely and provides a reference for the emergency rescue work

Chemical event tracking using a low-cost wireless chemical sensing network

A recently developed low-cost light emitting diode (LED) chemical sensing technique is integrated with a Mica2Dot wireless communications platform to form a deployable wireless chemical event indicator network. The operation of the colorimetric sensing node has been evaluated to determine its reproducibility and limit of detection for an acidic airborne contaminant. A test-scale network of five similar chemical sensing nodes is deployed in a star communication topology at fixed points within a custom built Environmental Sensing Chamber (ESC). Presented data sets collected from the deployed wireless chemical sensor network (WCSN) show that during an acidic event scenario it is possible to track the plume speed and direction, and estimate the concentration of chemical plume by examining the collective sensor data relative to individual sensor node location within the monitored environment

Hierarchical Leak Detection and Localization Method in Natural Gas Pipeline Monitoring Sensor Networks

In light of the problems of low recognition efficiency, high false rates and poor localization accuracy in traditional pipeline security detection technology, this paper proposes a type of hierarchical leak detection and localization method for use in natural gas pipeline monitoring sensor networks. In the signal preprocessing phase, original monitoring signals are dealt with by wavelet transform technology to extract the single mode signals as well as characteristic parameters. In the initial recognition phase, a multi-classifier model based on SVM is constructed and characteristic parameters are sent as input vectors to the multi-classifier for initial recognition. In the final decision phase, an improved evidence combination rule is designed to integrate initial recognition results for final decisions. Furthermore, a weighted average localization algorithm based on time difference of arrival is introduced for determining the leak point’s position. Experimental results illustrate that this hierarchical pipeline leak detection and localization method could effectively improve the accuracy of the leak point localization and reduce the undetected rate as well as false alarm rate

Design and implementation of an oil leakage monitoring system based on wireless network

Monitoring pipeline leaks is one of the recent hot studies. Leakage may occur because of time corrosion in the tube raw materials. To reduce the negative consequences of this leak, an effective leak detection system is used to prevent serious leakage accidents and damage in oil pipelines. Buildings, ecosystems, air pollution, and human life are all at risk in case of leakage occurs which could lead to fires. This paper introduces one of the research methods for the detection of pipeline leaks with a particular focus on software-based methods. The computer board interface (CBI) and wireless sensor networks have been used beside Arduino as a micro-monitor for the entire system. ZigBee is also utilized to send read data from sensors to the monitoring system displayed on the LabVIEW graphical user interface (GUI). The operator can take direct action when a leak occurs. The effectiveness of the leakage monitoring process and its practical use are demonstrated by the introduction of computerized techniques based on pressure gauge analysis on a specific pipeline in the laboratory. The result showed that the system is widely covered, accurate data transmission and robust real-time performance which reduces economic losses and environmental pollution

Framework for integrated oil pipeline monitoring and incident mitigation systems

Wireless Sensor Nodes (motes) have witnessed rapid development in the last two decades. Though the design considerations for Wireless Sensor Networks (WSNs) have been widely discussed in the literature, limited investigation has been done for their application in pipeline surveillance. Given the increasing number of pipeline incidents across the globe, there is an urgent need for innovative and effective solutions for deterring the incessant pipeline incidents and attacks. WSN pose as a suitable candidate for such solutions, since they can be used to measure, detect and provide actionable information on pipeline physical characteristics such as temperature, pressure, video, oil and gas motion and environmental parameters. This paper presents specifications of motes for pipeline surveillance based on integrated systems architecture. The proposed architecture utilizes a Multi-Agent System (MAS) for the realization of an Integrated Oil Pipeline Monitoring and Incident Mitigation System (IOPMIMS) that can effectively monitor and provide actionable information for pipelines. The requirements and components of motes, different threats to pipelines and ways of detecting such threats presented in this paper will enable better deployment of pipeline surveillance systems for incident mitigation. It was identified that the shortcomings of the existing wireless sensor nodes as regards their application to pipeline surveillance are not effective for surveillance systems. The resulting specifications provide a framework for designing a cost-effective system, cognizant of the design considerations for wireless sensor motes used in pipeline surveillance