Pengawasan Sistem Pigging Cerdas pada Pemeriksaan Pipa Saluran Bahan Bakar dari Tangki Penampung ke Terminal Pengisian
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Sistem intelligent pigging telah muncul sebagai teknologi penting untuk inspeksi in-line (ILI) pada jaringan pipa. Makalah ini memfokuskan ILI pada jaringan pipa bahan bakar hilir dari tangki penyimpanan ke stasiun pengisian. Makalah ini menawarkan metode non-intrusif untuk menilai integritas struktural, mendeteksi anomali, dan memastikan keselamatan operasional. Studi ini menyelidiki mekanisme sistem pemeriksaan pigging cerdas, dengan fokus pada akuisisi data dengan waktu yang tepat, pelayanan akurat, dan pengawasan adaptif dalam jaringan pipa yang kompleks. Sistem ini menggabungkan beberapa pengandaian penginderaan melalui kebocoran fluks magnetik (MFL) untuk memungkinkan memeriksa dalam pipa secara menyeluruh. Penekanan ditempatkan pada perancangan pengawasan algoritma yang mengelola kecepatan pig, menghubungkan sensor, dan perundingan rintangan dalam berbagai kondisi pipa bahan bakar. MFL berkaitan dengan pemrosesan sinyal, efisiensi daya dan komunikasi data di lingkungan yang terbatas. Hasil MFL menunjukkan metoda pengawasan efektif yang diusulkan dalam meningkatkan penemuan akurat dan keandalan operasional. Hasilnya menunjukan peningkatan manajemen integritas pipa dan mendukung praktik pemeliharaan prediktif di sektor transportasi bahan bakar.
Intelligent Pigging System Supervision in Inspection of Fuel Line Pipeline from Storage Tank to Filling Terminal
Abstract
Intelligent pigging systems have emerged as an important technology for in-line inspection (ILI) of pipelines. This paper focuses on ILI in downstream fuel pipelines from storage tanks to filling stations. It proposes a non-intrusive method to assess structural integrity, detect anomalies, and ensure operational safety. This study investigates the mechanism of an intelligent pigging inspection system, focusing on timely data acquisition, accurate service, and adaptive monitoring in complex pipelines. The system combines multiple sensing modalities via magnetic flux leakage (MFL) to enable comprehensive in-pipe inspection. Emphasis is placed on designing a monitoring algorithm that manages pig speed, sensor coupling, and obstacle negotiation under various fuel pipeline conditions. MFL deals with signal processing, power efficiency, and data communication in a confined environment. The MFL results demonstrate the effectiveness of the proposed monitoring method in improving accurate detection and operational reliability. The results demonstrate the improvement of pipeline integrity management and support predictive maintenance practices in the fuel transportation sector.
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