Intelligent audio processing methodology for operational risk reduction in complex industrial process control systems

Intelligent audio processing methodology for operational risk reduction in complex industrial process control systems

연구 분야: Infrastructure

학회: The Journal of Supercomputing

This study presents an innovative audio processing strategy that integrates ambient sound with headset audio to enhance situational awareness in dynamic environments, with potential applications in process control and monitoring systems. Our proposed methodology offers a systematic approach to extracting crucial environmental audio signals and seamlessly integrating them with headset audio content. Through comprehensive simulation studies across three industrial noise scenarios (quiet control room: 50 dBA, production floor: 70 dBA, machinery room: 90 dBA), our method demonstrates superior performance compared to baseline approaches. Specifically, the proposed system achieves significant improvements in signal-to-noise ratio (5–10 dB gain), perceptual evaluation of speech quality (PESQ scores of 3.21 vs. 2.43 for baseline Multi-channel Wiener Filter), short-time objective intelligibility (STOI values of 0.91 vs. 0.78), and signal-to-distortion ratio (16.8 dB vs. 11.3 dB). The system maintains real-time processing capabilities with a real-time factor (RTF) of 0.42 and memory requirements of 127 MB, making it suitable for embedded industrial systems. Validation using real-world industrial recordings from automotive manufacturing facilities confirms practical effectiveness with signal-to-distortion ratio of 7.82 dB and PESQ score of 3.24. The adaptive mixing algorithm and semi-supervised learning techniques enable the system to effectively model and adapt to various acoustic environments, making it suitable for deployment in diverse process control scenarios from petrochemical plants to manufacturing facilities. This research contributes to the field of process control by introducing a novel solution for maintaining operator awareness of critical auditory cues in complex industrial settings, where the ability to perceive and respond to environmental changes is essential for safety and efficiency.