Article
Engineering, Electrical & Electronic
Jae Cheol Lee, You Rak Choi, Jai Wan Cho
Summary: In this study, two ultrasonic leak detectors were developed for remote pipe leak detection using a non-contact, non-destructive method. One detector utilized a parabolic reflector while the other used a conical horn guide. The detectors were tested and evaluated outdoors according to ASTM E1002-05 class II standards for equipment verification. The results showed that the ultrasonic leak detector with the parabolic reflector had an average S/N ratio of 4.97 dB, while the detector with the conical horn guide had an average leak detection S/N ratio of 1.89 dB.
SENSORS AND ACTUATORS A-PHYSICAL
(2023)
Article
Engineering, Environmental
Song Yanjue, Li Suzhen
Summary: This paper presents a gas leak detection method for galvanised steel pipe based on acoustic emission, which shows strong robustness to internal flow noise and achieves over 93% overall accuracy when the leak rate is greater than 0.03 L/s in both the test set and cross-validation set.
PROCESS SAFETY AND ENVIRONMENTAL PROTECTION
(2021)
Article
Engineering, Mechanical
Zahoor Ahmad, Tuan-Khai Nguyen, Akhand Rai, Jong-Myon Kim
Summary: This paper proposes a novel technique for leak detection and localization in industrial fluid pipelines. The method utilizes acoustic emission signals and a multiscale Mann-Whitney test for leak detection, and a newly developed method called acoustic emission event tracking for leak localization. The results demonstrate that this method outperforms reference methods in terms of accuracy for leak detection and localization under variable pressure and leak conditions.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
(2023)
Article
Management
Victor Blanco, Miguel Martinez-Anton
Summary: In this paper, a mathematical optimization-based framework is proposed to determine the location of leak detection devices along a network. Two different models are analyzed, aiming to minimize the number of devices or maximize the coverage volume. Unlike other approaches, the models in this paper allow for flexible coverage by assuming devices are located in the whole space. Experimental results on real-world water supply pipeline networks support the validity of the proposed models.
OMEGA-INTERNATIONAL JOURNAL OF MANAGEMENT SCIENCE
(2024)
Article
Chemistry, Analytical
Niamat Ullah, Zahoor Ahmed, Jong-Myon Kim
Summary: Pipelines are important for distributing liquid and gas resources, but leaks can lead to resource waste, health risks, distribution downtime, and economic loss. This article proposes a machine learning-based platform that uses acoustic emission (AE) technology to detect pinhole-sized leaks. Statistical features extracted from the AE signal are used to train machine learning models. The proposed platform achieves an exceptional overall classification accuracy of 99% for detecting leaks and pinhole-sized leaks.
Article
Engineering, Multidisciplinary
Chi Zhang, Bradley J. Alexander, Mark L. Stephens, Martin F. Lambert, Jinzhe Gong
Summary: The implementation of a smart water network is an effective approach to address challenges faced by water utilities. This paper develops a CNN-based model to classify acoustic wave files collected by the SWN and extract features using transfer learning. The developed models have been validated and shown to be an effective tool for water pipeline leak and crack detection, enabling proactive management of pipeline assets.
STRUCTURAL HEALTH MONITORING-AN INTERNATIONAL JOURNAL
(2023)
Article
Engineering, Mechanical
Laurent Maxit, Mahmoud Karimi, Oriol Guasch, Frederic Michel
Summary: This study focuses on a monitoring technique based on vibration measurements to identify the presence of an acoustic source in a fluid-filled pipe with turbulent flow. The problem is complex due to fluid-structure coupling and the presence of resonant modes and internal flow excitations. Numerical vibroacoustic methods are used to predict the vibratory response of a pipe excited by a monopole source and/or a turbulent boundary layer (TBL). The performance of two vibroacoustic beamforming techniques is assessed using cross spectral matrices of computed radial accelerations. The results show that the MaxSNR approach outperforms the conventional approach in terms of array gain.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
(2022)
Article
Acoustics
Marshal Deep Kafle, Stanley Fong, Sriram Narasimhan
Summary: Water distribution systems are essential for society, but pipes are prone to leaks and bursts, which can be detected and localized using passive or active acoustic methods. This study presents a novel active method that relies on low-frequency sound waves in water pipes for leak detection and localization. By statistically treating time delays associated with multiple acoustic paths, leaks in plastic pipes can be accurately detected and localized.
Article
Engineering, Electrical & Electronic
Thang Bui Quy, Jong-Myon Kim
Summary: This article proposes a novel technique for pipeline leak detection by combining a Kalman filter and an outlier removal technique to estimate the true state, achieving higher detection rates compared to existing methods. The proposed method can achieve real-time leak detection.
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT
(2022)
Article
Engineering, Multidisciplinary
Zhiyuan Zhang, Changhang Xu, Jing Xie, Yuan Zhang, Pengqian Liu, Zichen Liu
Summary: Due to the complicated flow state of two-phase gas-liquid flows, existing leak detection techniques are not suitable for these pipelines. To prevent accidents caused by leaks, a framework combining Mel-frequency cepstral coefficient and long short-term memory based on acoustic emission (AE) is proposed. Experiments considering various operating conditions demonstrate that the MFCC-LSTM framework achieves a recognition accuracy of 98.4%. Furthermore, the framework exhibits excellent performance in leak size identification under different flow patterns.
Article
Chemistry, Analytical
Akhand Rai, Zahoor Ahmad, Md Junayed Hasan, Jong-Myon Kim
Summary: Pipeline leakage is a challenge in various industries, and the acoustic emission (AE) technology with AEE features and KS test is proposed as an effective method to accurately detect leaks.
Article
Chemistry, Analytical
Sajjad Ahmad, Zahoor Ahmad, Cheol-Hong Kim, Jong-Myon Kim
Summary: This paper proposes a reliable technique for pipeline leak detection using acoustic emission signals. The technique extracts global and local features from acoustic images obtained through continuous wavelet transform, and applies a shallow artificial neural network to identify the pipeline leak state.
Article
Engineering, Multidisciplinary
Naser Moosavian, Maziar Kasaei, Babak K. Roodsari
Summary: Finding the position and quantity of leakage in old water pipelines is challenging. Previous studies relied on large sample measurements, which are impractical. We proposed an efficient model combining ANFIS and ICA techniques to reduce the number of required samples. ANFIS approximates leak locations and quantities, while ICA corrects its estimations, leading to improved accuracy and reduced computational time.
Article
Engineering, Multidisciplinary
Wenming Wang, Haibo Sun, Jianqiang Guo, Liyun Lao, Shide Wu, Jifeng Zhang
Summary: Water pipeline leakage is a common global issue, and in-pipe inspection using hydrophones is an accurate method for leak detection. Experimental results show differences in signal intensity between leak and no leak conditions, and an artificial neural network model was developed for leak prediction with a maximum relative error within 10.0%, indicating reasonable accuracy for leak recognition.
Article
Engineering, Civil
Lingchun Zhang, Haiming Jiang, Junxi Zhang, Haitao Chen, Haimin Lu, Jianquan Li, Zhijia Hu, Kang Xie
Summary: Acoustic detection is a significant method for leak detection in water supply pipelines, but theoretical investigation and development are still limited. This study proposes a quantitative acoustic model for leak detection by combining liquid pipeline leaks with piston acoustics. The results indicate that leak sound pressure increases with pipeline pressure and decreases with detection distance, while the pipe material has little influence on the sound pressure.
JOURNAL OF PIPELINE SYSTEMS ENGINEERING AND PRACTICE
(2023)
Article
Automation & Control Systems
Ivo Campione, Cristiano Fragassa, Alberto Martini
INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY
(2019)
Article
Materials Science, Characterization & Testing
A. Steinwolf, B. Cornelis, B. Peeters, H. Van der Auweraer, A. Rivola, M. Troncossi
JOURNAL OF TESTING AND EVALUATION
(2020)
Article
Engineering, Mechanical
Alberto Martini, Marco Troncossi, Alessandro Rivola
MECHANISM AND MACHINE THEORY
(2019)
Article
Engineering, Mechanical
Marco Troncossi, Giulio Canella, Nicolo Vincenzi
Summary: This study focuses on the damping properties of a commercial polymer concrete and its potential as a filler material for machine bed components. The research aimed to quantitatively evaluate the elastodynamic effects and determine reliable material models to simulate the dynamic response of new machine design solutions. The results suggest that polymer concrete could be a viable solution for enhancing the dynamic behavior of automatic machines.
PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART C-JOURNAL OF MECHANICAL ENGINEERING SCIENCE
(2022)
Article
Chemistry, Multidisciplinary
Marco Troncossi, Sara Taddia, Alessandro Rivola, Alberto Martini
APPLIED SCIENCES-BASEL
(2020)
Article
Chemistry, Analytical
Francesco Falcetelli, Alberto Martini, Raffaella Di Sante, Marco Troncossi
Summary: This paper critically reviews the advantages and challenges of SMT in the automotive industry, and presents a case study to demonstrate its potential application in automotive modal analysis.
Article
Engineering, Electrical & Electronic
Alberto Martini, Giovanni Paolo Bonelli, Alessandro Rivola
Proceedings Paper
Energy & Fuels
Bengt E. G. Fallenius, Ramis Orlu, Gabriele Bellani, Alberto Martini, Marco Troncossi, Lucia Mascotelli, Jens H. M. Fransson, Alessandro Talamelli, P. Henrik Alfredsson
PROGRESS IN TURBULENCE VIII
(2019)
Article
Engineering, Marine
Cristofer H. Marques, Jean-D Caprace, Carlos R. P. Belchior, Alberto Martini
JOURNAL OF MARINE SCIENCE AND ENGINEERING
(2019)
Article
Engineering, Mechanical
Vuslat Odabasi, Stefano Maglio, Alberto Martini, Silvio Sorrentino
