{"id":11703,"date":"2026-09-11T17:17:13","date_gmt":"2026-09-11T09:17:13","guid":{"rendered":"\/jase\/?post_type=tkuisotope&p=11703"},"modified":"2026-09-11T20:04:42","modified_gmt":"2026-09-11T12:04:42","slug":"jase-202612-35-033","status":"publish","type":"tkuisotope","link":"\/jase\/?tkuisotope=jase-202612-35-033","title":{"rendered":"Design and Rationality of Natural Gas Dispatching System Architecture Using Voice Control Instructions with Unique-Id for Improving Traceability"},"content":{"rendered":"\n
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<\/i> 2026<\/a><\/p>\n<\/div>\n\n\n\n

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<\/i> Volume 35<\/a><\/p>\n<\/div>\n\n\n\n

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Hongtao Diao, Yu Li, Zengrui wang, Youyi Liang, Yi Yang<\/i><\/a><\/p>\n\n\n\n

Pipe China Oil & Gas Control Center, Beijing, 100013 China<\/p>\n<\/div>\n\n\n\n

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Received: July 13, 2026
Accepted: August 22, 2026
Publication Date: September 11, 2026<\/p>\n<\/div>\n<\/div>\n\n\n\n

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Block diagram of the proposed framework. <\/p>\n<\/div>\n<\/div>\n\n\n\n

<\/i> Copyright <\/strong>The Author(s). This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0)<\/a>, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are cited.<\/p>\n\n\n\n

Download Citation: BibTeX <\/a>| http:\/\/dx.doi.org\/10.6180\/jase.202612_35.033<\/a> <\/p>\n\n\n\n

Download PDF<\/a><\/p>\n\n\n\n

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Natural gas dispatching (NgD) systems increasingly employ voice control instructions to improve operational efficiency and human-machine interaction. However, existing voice-command frameworks lack end-to-end command traceability, limiting failure localization and compromising operational reliability and cybersecurity. This study proposes a natural gas dispatching system architecture that integrates unique identifiers with voice control instructions to enhance command traceability, authentication, and secure execution. The proposed framework assigns a unique ID to each voice command and integrates Exponential Growth Spectral Subtraction (EG-SS) for industrial noise suppression, Gaussian Mixture Model (GMM)-based speech recognition, Grunwald-Letnikov Secure Hash Algorithm-3 (GL-SHA-3) for command integrity verification, Consensus Finite State Machine (C-FSM) for operational limit validation, and SSG-aSiLUGRU for intent recognition and attack detection within the SCADA environment. Experimental results using voice command data and the SCADA Cybersecurity Research dataset collected from a simulated SCADA environment demonstrate that the proposed framework achieves 98.945% intent recognition and attack detection accuracy, a 20.5 dB Noise Reduction Ratio, 32 dB Signal-to-Noise Ratio, 687 ms hash creation time, 654 ms hash verification time, and 98.46% state transition accuracy, outperforming conventional approaches. These findings confirm that the proposed architecture effectively enhances command integrity, enables precise failure localization, strengthens cybersecurity against malicious voice-command attacks, and improves the reliability, safety, and traceability of natural gas dispatching operations.<\/p>\n\n\n\n

Keywords: Natural gas Dispatching (NgD) System, Voice Control Instructions (VCI), Traceability, Intent Recognition, Supervisory Control and Data Acquisition (SCADA).<\/em><\/p>\n\n\n\n

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