Applications of Z-Numbers and Neural Networks in Engineering

Jafari, Raheleh; Razvarz, Sina; Gegov, Alexander

doi:10.1007/978-3-030-52243-8_2

Cited by 5 publications

(6 citation statements)

References 42 publications

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“…Artificial intelligence has become the most effective approach which attracts many investigators to deeply research [20][21][22][23][24][25]. It has been successfully used for leak detection.…”

Section: Takedownmentioning

confidence: 99%

Pipeline Leak Detection and Location based on Fuzzy Controller

Razvarz

Jafari

Vargas-Jarillo

et al. 2020

2020 IEEE Symposium Series on Computational Intelligence (SSCI)

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Pipeline systems have been taken as one of the most important tools for transmission around the world. It will be important for the industrial society that pipeline systems function appropriately by taking into consideration the growing requirement for effective interconnecting fluid networks. Typically, there are various kinds of control systems or algorithms for pipeline leak detection. In this paper, a pipeline leak detection and location method is proposed based on fuzzy control. It is concluded that the response of the fuzzy controller is fast and has no oscillations and this is appropriate for numerous high-precision usages like robotics as well as weapon systems. The numerical results demonstrate that the suggested technique is simple, efficient, and has a high level of localization precision.

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Section: Takedownmentioning

confidence: 99%

Pipeline Leak Detection and Location based on Fuzzy Controller

Razvarz

Jafari

Vargas-Jarillo

et al. 2020

2020 IEEE Symposium Series on Computational Intelligence (SSCI)

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“…In [11], a new method based on auxiliary mass spatial probing by the stationary wavelet transform is suggested to detect damage in beams. Artificial intelligence with fuzzy logic has become the most effective approach, which attracts many investigators to deeply research it [12][13][14][15][16]. It has been successfully used for leak detection.…”

Section: Introductionmentioning

confidence: 99%

“…It has been successfully used for leak detection. In [17], a low-cost wireless sensor system it [12][13][14][15][16]. It has been successfully used for leak detection.…”

Section: Introductionmentioning

confidence: 99%

Pipeline Leak Detection and Estimation Using Fuzzy PID Observer

et al. 2022

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A pipe is a ubiquitous product in the industries that is used to convey liquids, gases, or solids suspended in a liquid, e.g., a slurry, from one location to another. Both internal and external cracking can result in structural failure of the industrial piping system and possibly decrease the service life of the equipment. The chaos and complexity associated with the uncertain behaviour inherent in pipeline systems lead to difficulty in detection and localisation of leaks in real time. The timely detection of leakage is important in order to reduce the loss rate and serious environmental consequences. The objective of this paper is to propose a new leak detection method based on an autoregressive with exogenous input (ARX) Laguerre fuzzy proportional-integral-derivative (PID) observation system. The objective of this paper is to propose a new leak detection method based on an autoregressive with exogenous input (ARX) Laguerre fuzzy proportional-integral-derivative (PID) observation system. In this work, the ARX–Laguerre model has been used to generate better performance in the presence of uncertainty. According to the results, the proposed technique can detect leaks accurately and effectively.

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“…In [11] the cepstrum method is used to analyse a series of different pipe networks, both with and without leaks. Fuzzy logic and artificial intelligence techniques have been used successfully in many real-world applications [12][13][14][15][16][17]. They have been used for leak detection in water networks as well as in the oil and gas industry.…”

Section: Introductionmentioning

confidence: 99%

“…In [20] and [21] neural network method has been proposed for the purpose of detecting and localizing leakage in pipeline. In [12,[22][23][24] neural network technique is used for detection of the gas leakage in pipeline. In [20] a fault detection model based on multi-layer neural network using data mining technique is used for pattern recognition in oil pipe networks [24][25][26][27].…”

Section: Introductionmentioning

confidence: 99%

Leakage Detection for Pipe Systems with Fuzzy Monitoring Strategy

Jafari

Razvarz

Vargas-Jarillo

et al. 2021

2021 IEEE Symposium Series on Computational Intelligence (SSCI)

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A Pipe is a ubiquitous product in the industries that is used to convey liquids, gases, or solids suspended in a liquid, e.g., a slurry from one location to another. Both internal and external cracking can result in structural failure of the industrial piping system and possibly decrease the service life of the equipment. The chaos and complexity associated with the uncertain behavior inherent in pipeline systems lead to difficulty in detection and localisation of leaks in real-time. The timely detection of leakage is important in order to reduce the loss rate and serious environmental consequences. To address this issue, in this paper an auto regressive with exogenous input (ARX)-Laguerre fuzzy proportional -derivative (PD) observation system is pro-posed to detect and estimate a leak in pipelines. In this work, the ARX-Laguerre model has been used to generate better performance in the presence of uncertainty. According to the results, the proposed technique can detect leaks accurately and effectively.

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Applications of Z-Numbers and Neural Networks in Engineering

Cited by 5 publications

References 42 publications

Pipeline Leak Detection and Location based on Fuzzy Controller

Pipeline Leak Detection and Location based on Fuzzy Controller

Pipeline Leak Detection and Estimation Using Fuzzy PID Observer

Leakage Detection for Pipe Systems with Fuzzy Monitoring Strategy

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