Article
Chemistry, Multidisciplinary
Yao-Long Tsai, Hung-Chih Chang, Shih-Neng Lin, Ai-Huei Chiou, Tin-Lai Lee
Summary: To address the challenges brought by abnormal weather and industrial water consumption in Taiwan, the government has implemented measures such as transporting water and investing in backup water pipelines. However, the high leakage rate of water pipelines remains a concern. This study developed an intelligent sound-assisted water leak identification system using artificial intelligence and IoT technology, which has shown high accuracy and reliability in identifying and locating leaks.
APPLIED SCIENCES-BASEL
(2022)
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, Multidisciplinary
Li Ai, Mahmoud Bayat, Paul Ziehl
Summary: Nuclear power generation is crucial for the US electrical supply and achieving low carbon power generation. Improper disposal or storage of spent radioactive fuel can have detrimental effects on the environment and human health. This paper presents an innovative method utilizing acoustic emission (AE) and data fusion to precisely detect and locate damage in storage canisters, using a minimal number of AE sensors.
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, Multidisciplinary
Zahoor Ahmad, Tuan-Khai Nguyen, Jong-Myon Kim
Summary: This paper proposes a leak detection and size identification technique in fluid pipelines based on a new leak-sensitive feature called the vulnerability index (VI) and 1-D convolutional neural network (1D-CNN). The technique extracts acoustic emission hit features and applies a multiscale Mann-Whitney test to obtain the vulnerability index feature, which shows the pipeline's susceptibility to leak and changes according to the pipeline working conditions. Experimental results demonstrate that the proposed method outperforms state-of-the-art methods under variable fluid pressure conditions.
ENGINEERING APPLICATIONS OF COMPUTATIONAL FLUID MECHANICS
(2023)
Article
Engineering, Multidisciplinary
Shen-Bin Zhu, Zhen-Lin Li, Xiang Li, Hao-hao Xu, Xi-ming Wang
Summary: The traditional methods for diagnosing valve internal leakage have limitations, leading to the proposal of a new method using convolutional neural networks to recognize valve internal leakage. Experimental results show that this method can effectively identify internal leakage signals, with a maximum prediction error of less than 3%, serving as a new approach for valve leakage diagnosis.
Article
Mathematics
Fuxing Yu, Zhihu Qin, Ruina Li, Zhanlin Ji
Summary: This study proposes a new method for steel pipe size measurements based on edge extraction and image processing to address the issues of low accuracy and labor waste in construction steel pipe inspection. By using convolutional neural network technology, the dataset scale and image scale were improved, and the error value of the Hough transform was effectively reduced.
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
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
Materials Science, Characterization & Testing
Shaofeng Wang, Lili Dong, Jianguo Wang, Hailing Wang, Guang Xu, Jun Hong
Summary: This study investigates how to precisely locate the leak source on a gas-filled steel pipe by reconstructing the continuous leak acoustic emission signal. The results show that using the speed of the T wave for leak source localization provides better accuracy.
JOURNAL OF TESTING AND EVALUATION
(2021)
Article
Construction & Building Technology
Zewei Zhang, Leixia Zhang, Ming Fu, Didem Ozevin, Hongyong Yuan
Summary: As an integral part of a city's infrastructure, urban underground natural gas pipeline network plays a crucial role in energy transmission. This study presents a novel method for identifying leaks in buried gas pipelines by using leak noise in the surrounding soil. Experimental results show that the proposed method achieves accurate leak localization, with a maximum error rate of 12%.
TUNNELLING AND UNDERGROUND SPACE TECHNOLOGY
(2022)
Article
Engineering, Environmental
Alibek Kopbayev, Faisal Khan, Ming Yang, Syeda Zohra Halim
Summary: Detection and diagnosis of natural gas leakage is crucial for ensuring safety. This study combines a convolutional network and a bi-directional long short-term memory layer network to perform leak detection and diagnosis. The model successfully predicts gas leakage and classifies its size, showing promising results for early and accurate leak detection in natural gas facilities.
PROCESS SAFETY AND ENVIRONMENTAL PROTECTION
(2022)
Article
Engineering, Mechanical
Li Ai, Vafa Soltangharaei, Paul Ziehl
Summary: This paper develops an automatic ASR monitoring and evaluation approach by leveraging acoustic emission (AE) and a heterogeneous ensemble learning framework. Experimental results show that the proposed method can accurately classify AE signals into different ASR phases.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
(2022)
Article
Chemistry, Multidisciplinary
Muhammad Arslan, Khurram Kamal, Muhammad Fahad Sheikh, Mahmood Anwar Khan, Tahir Abdul Hussain Ratlamwala, Ghulam Hussain, Mohammed Alkahtani
Summary: This study presents a novel approach to monitoring the tool health of a CNC machine for a turning process using airborne acoustic emission and convolutional neural networks. Experimental results show that the proposed CNN architecture with four filters of size 5 x 5 achieves an average classification accuracy of 99.2% in classifying tool health into three categories of new, average, and worn-out tools.
APPLIED SCIENCES-BASEL
(2021)
Article
Engineering, Environmental
Fangli Ning, Zhanghong Cheng, Di Meng, Shuang Duan, Juan Wei
Summary: SE-CNN is a novel architecture that combines spectrum enhancement and convolutional neural network for gas pipeline leak detection, achieving high accuracy in leak diagnosis in a short time.
PROCESS SAFETY AND ENVIRONMENTAL PROTECTION
(2021)
Article
Engineering, Environmental
Xingxing Hu, Lingjie Liu, Yanmeng Bi, Lu Li, Chunsheng Qiu, Jingjie Yu, Shaopo Wang
Summary: In this study, the impact of exogenous folate on the start-up process of single-stage partial nitritation-anammox (SPNA) was evaluated using two lab-scale reactors. The results showed that folate addition can enhance nitrogen removal rate, extracellular polymeric substances production, hydrazine oxidase and dehydrogenase activity, as well as the relative abundance of Candidatus Brocadia.
PROCESS SAFETY AND ENVIRONMENTAL PROTECTION
(2024)
Article
Engineering, Environmental
Shaocang He, Tingting Shen, Jing Sun, Haoqi Pan, Chenxu Sun, Tianpeng Li, Runyao Li, Enshan Zhang
Summary: A novel process of acid leaching neutralization was developed for the preparation of inorganic polymeric composite ferric aluminum silicate coagulant (CFAS) using solid waste coal gasification coarse slag (CGCS). The optimized preparation process was determined through single-factor experiment and the performance of CFAS was evaluated for domestic sewage treatment. The results showed that CFAS exhibited excellent coagulation ability and achieved significant removal efficiency for turbidity, ammonia nitrogen, and chemical oxygen demand.
PROCESS SAFETY AND ENVIRONMENTAL PROTECTION
(2024)
Article
Engineering, Environmental
Kinga Szatmari, Sandor Nemeth, Alex Kummer
Summary: In this article, a resilience-based reinforcement learning approach is proposed to address the potential thermal runaway issue in batch reactors. By calculating the resilience metric for reactors and utilizing Deep Q-learning to decide when to intervene in the system, resilient-based mitigation systems can be effectively developed.
PROCESS SAFETY AND ENVIRONMENTAL PROTECTION
(2024)
Article
Engineering, Environmental
Bingyou Jiang, Qi Yao, Mingqing Su, Jingjing Li, Kunlun Lu, Dawei Ding, Han Hong
Summary: This study investigates the inhibitory characteristics and mechanisms of ABC powder on coal powder explosion. The addition of ABC powder significantly decreases the maximum explosion pressure and can completely suppress coal dust explosions. The study also reveals the thermal decomposition characteristics and reaction kinetics of the mixed system.
PROCESS SAFETY AND ENVIRONMENTAL PROTECTION
(2024)
Article
Engineering, Environmental
Kubilay Bayramoglu, Mustafa Nuran
Summary: This study examines the feasibility of using pyrolytic oil from waste tires as fuel in diesel engines, and evaluates its energy, exergy, and sustainability. The results indicate that pyrolytic oil has potential as a renewable fuel source with relatively high thermal efficiency.
PROCESS SAFETY AND ENVIRONMENTAL PROTECTION
(2024)
Article
Engineering, Environmental
Xinru Duan, Yejia Lv, Jiaxing Hong, Jianzhong Wu, Jia Zhang, Yang Yue, Guangren Qian
Summary: This study successfully prepared a tube reactor with optimized catalyst formula, which showed good performance in removing dioxins and other pollutants in the experiments.
PROCESS SAFETY AND ENVIRONMENTAL PROTECTION
(2024)
Article
Engineering, Environmental
Jiaoyang Du, Xueming Dang, Xiaorong Gan, Xin Cui, Huimin Zhao
Summary: In this study, a photocatalyst-enzyme hybrid system was constructed, which solved the issue of enzyme inactivation caused by high concentration of H2O2 through photocatalytic in-situ H2O2 production, and improved the stability and catalytic efficiency of the enzyme. The effectiveness of the system in treating phenolic EDCs was confirmed through experiments.
PROCESS SAFETY AND ENVIRONMENTAL PROTECTION
(2024)
Article
Engineering, Environmental
Fu-Rong Xiu, Longsheng Zhan, Yingying Qi, Xinyue Lei, Jiali Wang, Haipeng Zhou, Wenting Shao
Summary: This study developed a synergetic and high-efficiency treatment of waste tantalum capacitors (WTCs) and polyvinyl chloride (PVC) using subcritical water process. The treatment significantly reduced the temperature and reaction time for metal tantalum recovery from WTCs, and improved the dechlorination efficiency of PVC. The optimized conditions resulted in 100% resin conversion efficiency of WTCs and 97.39% dechlorination efficiency of PVC. The interaction between decomposition products of WTCs and PVC produced a high level of benzoic acid.
PROCESS SAFETY AND ENVIRONMENTAL PROTECTION
(2024)
Article
Engineering, Environmental
Bingda Li, Jiaming Song, Yuting Li, Chaoying Meng, Shuxian Wang, Linghao Zong, Honggang Ye, Yishuai Jing, Feng Teng, Peng Hu, Haibo Fan, Guangde Chen, Xin Zhao
Summary: CdPS3 nanosheets, especially those exfoliated by sodium cholate, have shown highly efficient photocatalytic degradation performance. The strong dark adsorption and dye-sensitized photocatalytic properties of CdPS3 nanosheets contribute to high degradation efficiencies of various pollutants.
PROCESS SAFETY AND ENVIRONMENTAL PROTECTION
(2024)
Article
Engineering, Environmental
Dongxu Ouyang, Yimei Pang, Bo Liu, Zhirong Wang
Summary: This study investigates the thermal runaway features of lithium-ion cells under tunnel conditions, considering different states of charge and tunnel ceilings. The results show that the tunnel visibility is affected by the smoke generated during thermal runaway, and the shape of the tunnel ceiling influences the temperature rise differently.
PROCESS SAFETY AND ENVIRONMENTAL PROTECTION
(2024)