Intelligent diagnosis of natural gas pipeline defects using improved flower pollination algorithm and artificial neural network

Liang, Xiaobin; Liang, Wei; Xiong, Jingyi

doi:10.1016/j.jclepro.2020.121655

Cited by 20 publications

(6 citation statements)

References 31 publications

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“…The FPA exhibits low search accuracy and slow convergence speed when applied to complex optimization problems (Zhou et al. , 2016; Liang et al. , 2020).…”

Section: Improved Flower Pollination Algorithmmentioning

confidence: 99%

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A novel robust design optimization method combining improved flower pollination algorithm and dual Kriging

Zhang,

Li,

Wang

et al. 2023

MMMS

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PurposeThis study aims to propose a more precise method for robust design optimization of mechanical structures with black-box problems, while also considering the efficiency of uncertainty analysis.Design/methodology/approachThe method first introduces a dual adaptive chaotic flower pollination algorithm (DACFPA) to overcome the shortcomings of the original flower pollination algorithm (FPA), such as its susceptibility to poor accuracy and convergence efficiency when dealing with complex optimization problems. Furthermore, a DACFPA-Kriging model is developed by optimizing the relevant parameter of Kriging model via DACFPA. Finally, the dual Kriging model is constructed to improve the efficiency of uncertainty analysis, and a robust design optimization method based on DACFPA-Dual-Kriging is proposed.FindingsThe DACFPA outperforms the FPA, particle swarm optimization and gray wolf optimization algorithms in terms of solution accuracy, convergence speed and capacity to avoid local optimal solutions. Additionally, the DACFPA-Kriging model exhibits superior prediction accuracy and robustness contrasted with the original Kriging and FPA-Kriging. The proposed method for robust design optimization based on DACFPA-Dual-Kriging is applied to the motor hanger of the electric multiple units as an engineering case study, and the results confirm a significant reduction in the fluctuation of the maximum equivalent stress.Originality/valueThis study represents the initial attempt to enhance the prediction accuracy of the Kriging model using the improved FPA and to combine the dual Kriging model for uncertainty analysis, providing an idea for the robust optimization design of mechanical structure with black-box problem.

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“…The FPA exhibits low search accuracy and slow convergence speed when applied to complex optimization problems (Zhou et al. , 2016; Liang et al. , 2020).…”

Section: Improved Flower Pollination Algorithmmentioning

confidence: 99%

“…The FPA exhibits low search accuracy and slow convergence speed when applied to complex optimization problems (Zhou et al, 2016;Liang et al, 2020). To address the limitations of the FPA, the proposed DACFPA makes improvements in the following aspects.…”

Section: Proposed Dual Adaptive Chaotic Flower Pollination Algorithmmentioning

confidence: 99%

A novel robust design optimization method combining improved flower pollination algorithm and dual Kriging

Zhang,

Li,

Wang

et al. 2023

MMMS

View full text Add to dashboard Cite

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“…Contact pressure, contact material and other factors should be considered when determining the contact radius r. The formula is shown in (10) :…”

Section: ) Electric Repulsionmentioning

confidence: 99%

“…Experiments show that the improved algorithm has higher optimization speed and solution accuracy. Liang XB et al [10] introduced Infinite Folding Iterative Chaos Mapping (ICMIC) in order to increase the diversity of the population, and introduced a comprehensive opposition (CO) learning strategy in order to enhance the algorithm's mining capabilities. The test function simulation proved that the improved algorithm is compared It has better performance than other algorithms.…”

Section: Introductionmentioning

confidence: 99%

Optimal Design of Circuit Breaker Based on Flower Pollination Algorithm

Xie

TIAN

2022

Preprint

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The flower pollination algorithm is a new meta-heuristic algorithm that simulates the pollination behavior of flowers in nature. Aiming at the problem that the basic flower pollination algorithm is easy to fall into the local optimum and the later convergence speed is slow, the "adaptive-mutation catfish" flower pollination algorithm is proposed, Introduce the adaptive step size in the global pollination stage, introduce the mutation strategy and catfish effect in the local pollination stage, and use the classic test function to analyze the performance of the improved algorithm. The improved flower pollination algorithm is applied to the high breaking and comprehensive optimization design of the circuit breaker, the mathematical model of the high breaking and comprehensive optimization of the circuit breaker is constructed, and the optimal design method of the circuit breaker based on the flower pollination algorithm is given. The results show that the circuit breaker optimization design method based on flower pollination algorithm is feasible, and the improved flower pollination algorithm is effective.

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“…In addition, with the rapid development and application of the Artificial Intelligent (AI) technology, the AI-related intelligent technology is also a potential research direction for the optimal estimation of the multi-sensor-fused intelligent PIG surveying system [ 96 , 97 , 98 , 99 ].…”

Section: Trends and Challenges For Small-diameter Intelligent Pig mentioning

confidence: 99%

A Comprehensive Review of Micro-Inertial Measurement Unit Based Intelligent PIG Multi-Sensor Fusion Technologies for Small-Diameter Pipeline Surveying

et al. 2020

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It is of great importance for pipeline systems to be is efficient, cost-effective and safe during the transportation of the liquids and gases. However, underground pipelines often experience leaks due to corrosion, human destruction or theft, long-term Earth movement, natural disasters and so on. Leakage or explosion of the operating pipeline usually cause great economical loss, environmental pollution or even a threat to citizens, especially when these accidents occur in human-concentrated urban areas. Therefore, the surveying of the routed pipeline is of vital importance for the Pipeline Integrated Management (PIM). In this paper, a comprehensive review of the Micro-Inertial Measurement Unit (MIMU)-based intelligent Pipeline Inspection Gauge (PIG) multi-sensor fusion technologies for the transport of liquids and gases purposed for small-diameter pipeline (D<30cm) surveying is demonstrated. Firstly, four types of typical small-diameter intelligent PIGs and their corresponding pipeline-defects inspection technologies and defects-positioning technologies are investigated according to the various pipeline defects inspection and localization principles. Secondly, the multi-sensor fused pipeline surveying technologies are classified into two main categories, the non-inertial-based and the MIMU-based intelligent PIG surveying technology. Moreover, five schematic diagrams of the MIMU fused intelligent PIG fusion technology is also surveyed and analyzed with details. Thirdly, the potential research directions and challenges of the popular intelligent PIG surveying techniques by multi-sensor fusion system are further presented with details. Finally, the review is comprehensively concluded and demonstrated.

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Intelligent diagnosis of natural gas pipeline defects using improved flower pollination algorithm and artificial neural network

Cited by 20 publications

References 31 publications

A novel robust design optimization method combining improved flower pollination algorithm and dual Kriging

A novel robust design optimization method combining improved flower pollination algorithm and dual Kriging

Optimal Design of Circuit Breaker Based on Flower Pollination Algorithm

A Comprehensive Review of Micro-Inertial Measurement Unit Based Intelligent PIG Multi-Sensor Fusion Technologies for Small-Diameter Pipeline Surveying

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